Autonomous Vehicle Operating Status Assessment

ABSTRACT

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status and/or configuration of autonomous operation features of an autonomous or semi-autonomous vehicle may be determined, such as via an on-board computer system or mobile device, and/or then directly or indirectly wirelessly communicated via data transmission from the vehicle computer system or mobile device to a remote server. An adjustment to one or more risk levels associated with operation of the autonomous or semi-autonomous vehicle may also be determined, and an auto insurance policy, premium, or discount may be adjusted based upon the adjustment to the risk levels and presented to the customer for their review and approval. As a result, insurance cost savings may be passed onto risk averse customers that opt into to a rewards program.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims the benefit of, U.S.patent application Ser. No. 14/934,326 filed Nov. 6, 2015, entitled“Autonomous Vehicle Operating Status Assessment,” which claims thebenefit of U.S. Provisional Application No. 62/079,533 (filed Nov. 13,2014); U.S. Provisional Application No. 62/103,831 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,836 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,838 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,840 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,855 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,856 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,891 (filed Jan. 15.2015); U.S. Provisional Application No. 62/103,893 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,895 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,907 (filed Jan. 15,2015); U.S. Provisional Application No. 62/103,911 (filed Jan. 15,2015); and U.S. Provisional Application No. 62/103,914 (filed Jan. 15,2015). The entirety of each of the foregoing applications isincorporated by reference herein.

Additionally, the present application is related to co-pending U.S.patent application Ser. No. 14/934,333 (filed Nov. 6, 2015); co-pendingU.S. patent application Ser. No. 14/931,339 (filed Nov. 6, 2015);co-pending U.S. patent application Ser. No. 14/934,343 (filed Nov. 6,2015); co-pending U.S. patent application Ser. No. 14/934,345 (filedNov. 6, 2015); co-pending U.S. patent application Ser. No. 14/934,347(filed Nov. 6, 2015); co-pending U.S. patent application Ser. No.14/934,352 (filed Nov. 6, 2015); co-pending U.S. patent application Ser.No. 14/934,355 (filed Nov. 6, 2015); co-pending U.S. patent applicationSer. No. 14/934,357 (filed Nov. 6, 2015); co-pending U.S. patentapplication Ser. No. 14/934,361 (filed Nov. 6, 2015); co-pending U.S.patent application Ser. No. 14/934,371 (filed Nov. 6, 2015); co-pendingU.S. patent application Ser. No. 14/934,381 (filed Nov. 6, 2015);co-pending U.S. patent application Ser. No. 14/934,385 (filed Nov. 6,2015); co-pending U.S. patent application Ser. No. 14/934,388 (filedNov. 6, 2015); co-pending U.S. patent application Ser. No. 14/934,393(filed Nov. 6, 2015); co-pending U.S. patent application Ser. No.14/934,400 (filed Nov. 6, 2015); and co-pending U.S. patent applicationSer. No. 14/934,405 (filed Nov. 6, 2015).

FIELD

The present disclosure generally relates to systems and methods foroperating, monitoring, assessing, or insuring autonomous orsemi-autonomous vehicles.

BACKGROUND

Vehicles are typically operated by a human vehicle operator who controlsboth steering and motive controls. Operator error, inattention,inexperience, misuse, or distraction leads to many vehicle accidentseach year, resulting in injury and damage. Autonomous or semi-autonomousvehicles augment vehicle operators' information or replace vehicleoperators' control commands to operate the vehicle in whole or part withcomputer systems based upon information from sensors within the vehicle.

Vehicle or automobile insurance exists to provide financial protectionagainst physical damage and/or bodily injury resulting from trafficaccidents and against liability that could arise therefrom. Typically, acustomer purchases a vehicle insurance policy for a policy rate having aspecified term. In exchange for payments from the insured customer, theinsurer pays for damages to the insured which are caused by coveredperils, acts, or events as specified by the language of the insurancepolicy. The payments from the insured are generally referred to as“premiums,” and typically are paid on behalf of the insured over time atperiodic intervals. An insurance policy may remain “in-force” whilepremium payments are made during the term or length of coverage of thepolicy as indicated in the policy. An insurance policy may “lapse” (orhave a status or state of “lapsed”), for example, when premium paymentsare not being paid or if the insured or the insurer cancels the policy.

Premiums may be typically determined based upon a selected level ofinsurance coverage, location of vehicle operation, vehicle model, andcharacteristics or demographics of the vehicle operator. Thecharacteristics of a vehicle operator that affect premiums may includeage, years operating vehicles of the same class, prior incidentsinvolving vehicle operation, and losses reported by the vehicle operatorto the insurer or a previous insurer. Past and current premiumdetermination methods do not, however, account for use of autonomousvehicle operating features. The present embodiments may, inter alia,alleviate this and/or other drawbacks associated with conventionaltechniques.

BRIEF SUMMARY

The present embodiments may be related to autonomous or semi-autonomousvehicle functionality, including driverless operation, accidentavoidance, or collision warning systems, These autonomous vehicleoperation features may either assist the vehicle operator to more safelyor efficiently operate a vehicle or may take full control of vehicleoperation under some or all circumstances. The present embodiments mayalso facilitate risk assessment and premium determination for vehicleinsurance policies covering vehicles with autonomous operation features.For instance, a consumer may opt-in to a rewards program that rewardsthem, such as in the form of insurance discounts, for sharing datarelated to their vehicles and/or autonomous features with an insuranceprovider.

In accordance with the described embodiments, the disclosure hereingenerally addresses systems and methods for determining the status ofautonomous operation features of an autonomous or semi-autonomousvehicle, which may include one or more sensors. A computer associatedwith the vehicle (such as an on-board computer, mobile device, or servercommunicatively connected to the vehicle) may (1) receive a signalindicating a request to determine an operating status of one or moreautonomous operation features of the autonomous or semi-autonomousvehicle; (2) determine a configuration of the one or more autonomousoperation features; (3) present or send a test signal to the one or moreautonomous operation features; (4) receive one or more response signalsfrom the one or more autonomous operation features (or associatedprocessors); (5) determine the operating status of the one or moreautonomous operation features based upon the received one or moreresponse signals; (6) generate an operating status report or electronicmessage indicating the operating status of the one or more autonomousoperation features, which may include a certification of the operatingstatus of the one or more autonomous operation features; (7) store theoperating status report in memory for subsequent use; and/or (8) presentthe operating status report to an insured or vehicle operator/owner. Insome embodiments, the computer may further (9) transmit the generatedoperating status report to a server, such as via wireless communicationor data transmission, whereupon the server may further receive one ormore indications of maintenance performed on the autonomous orsemi-autonomous vehicle, determine an adjustment to one or more risklevels associated with operation of the autonomous or semi-autonomousvehicle, determine an adjustment to a cost associated with an insurancepolicy associated with the autonomous or semi-autonomous vehicle basedupon the determined adjustment to the one or more risk levels and/orbased upon the received one or more indications of maintenance, and/orcause the adjustment to the cost associated with the insurance policy tobe implemented. The cost associated with the insurance policy mayinclude one or more of the following: a premium, a discount, asurcharge, a rate level, a cost based upon a distance traveled, a costbased upon a vehicle trip, and/or a cost based upon a duration ofvehicle operation.

In some embodiments, the signal indicating the request to determine theoperating status of the one or more autonomous operation features may beautomatically generated upon the occurrence of an event, including oneor more of the following: receipt of a command to start the vehicle,receipt of a command to shut off the vehicle, receipt of an indicationof a collision involving the vehicle, or receipt of an indication ofdamage to the vehicle. The signal may be received from a mobile deviceor from a special-purpose computing device communicatively connected tothe autonomous or semi-autonomous vehicle.

In further embodiments, the computer may attempt to diagnose and/orcorrect problems with autonomous operation features. When the operationof one or more sensors disposed within the vehicle are determined to beimpaired by environmental factors (including snow, ice, rain, dirt, mud,or condensation), a remediation module may generate a remediationsignal, which may be presented to one or more remediation componentsdisposed within the vehicle. The remediation components may beconfigured to remediate impairments of the one or more sensors byenvironmental factors, A system status module may likewise diagnose oneor more errors with at least one autonomous operation feature based uponthe received one or more response signals from the one or moreautonomous operation features, in order to correct the diagnosed one ormore errors with the at least one autonomous operation feature.Correcting the diagnosed one or more errors with the at least oneautonomous operation feature may include calibrating at least one sensordisposed within the vehicle based upon the received one or more responsesignals from the one or more autonomous operation features.

In accordance with the described embodiments, the disclosure hereinfurther generally addresses systems and methods for real-time (or nearreal-time) determination of the status of autonomous operation featuresof an autonomous or semi-autonomous vehicle, which may include one ormore sensors. A computer (such as an on-board computer, mobile device,or server communicatively connected to the vehicle) associated with thevehicle may (1) monitor the operation of the autonomous orsemi-autonomous vehicle to obtain operating data from one or moreautonomous operation features; (2) determine an operating status of theone or more autonomous operation features of the autonomous orsemi-autonomous vehicle based upon the operating data; (3) determine achange in the operating status of the one or more autonomous operationfeatures based upon the determined operating status; (4) generate areport containing information regarding the change in the operatingstatus of the one or more autonomous operation features; (5) store theoperating status report in memory for subsequent use, such as the usesdiscussed herein, as well as directly below, and/or (6) present theoperating status report or information based upon the operating statusreport to an insured or vehicle operator/owner.

In some embodiments, the computer may further determine an adjustment toa cost associated with an insurance policy associated with theautonomous or semi-autonomous vehicle based upon the determined changein the operating status of the one or more autonomous operationfeatures, and/or cause the adjustment to the cost associated with theinsurance policy to be implemented. Determining the adjustment to thecost associated with the insurance policy may include determining anadjustment to a risk associated with operation of the autonomous orsemi-autonomous vehicle based upon the determined change in theoperating status of the one or more autonomous operation features. Thecost associated with the insurance policy may include one or more of thefollowing: a premium, a discount, a surcharge, a rate level, a costbased upon a distance traveled, a cost based upon a vehicle trip, and/ora cost based upon a duration of vehicle operation.

In further embodiments, the computer may determine that the change inoperating status of the one or more autonomous operation features maycause the operating status of the one or more autonomous operationfeatures to pass an alert threshold, in which case an alert indicatingan impairment of the operation of the one or more autonomous operationfeatures may be generated and presented to a person associated with theautonomous or semi-autonomous vehicle. Additionally, or alternatively,the computer may determine that the change in operating status of theone or more autonomous operation features may cause the operating statusof the one or more autonomous operation features to pass a criticalthreshold, in which case control of the autonomous or semi-autonomousvehicle may be transferred to a vehicle operator. If the computerfurther determines that control of the autonomous or semi-autonomousvehicle cannot safely be transferred to a vehicle operator, however, theautonomous or semi-autonomous vehicle may stop and discontinueoperation.

In each of the embodiments or aspects described above, the methods maybe provided in corresponding computer systems including at least one ormore processors and a non-transitory program memory coupled to the oneor more processors and storing executable instructions. The computersystems may further include or be communicatively connected to one ormore sensors, communication components or devices, or other equipment asdescribed herein. In yet another aspect, a tangible, non-transitorycomputer-readable medium storing instructions corresponding to each ofthe embodiments or aspects described above may be provided. Each of themethods or executable instructions of the computer systems orcomputer-readable media may include additional, fewer, or alternateactions, including those discussed elsewhere herein.

Methods and systems for monitoring use, determining risk, and pricinginsurance policies for a vehicle having one or more autonomous orsemi-autonomous operation features are provided. According to certainaspects, the operating status and/or configuration of autonomousoperation features of an autonomous or semi-autonomous vehicle may bedetermined, such as via an on-board computer system or mobile device,and/or then wirelessly communicated via data transmission from thevehicle computer system or mobile device to a remote server. Anadjustment to one or more risk levels associated with operation of theautonomous or semi-autonomous vehicle may also be determined, and anauto insurance policy, premium, or discount may be adjusted based uponthe determined adjustment to the one or more risk levels and presentedto the customer for their review and approval. In some embodiments,insurance cost savings may be passed onto risk averse customers thatopt-in to a rewards or other insurance-based program.

BRIEF DESCRIPTION OF THE DRAWINGS

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

The figures described below depict various aspects of the applications,methods, and systems disclosed herein. It should be understood that eachfigure depicts an embodiment of a particular aspect of the disclosedapplications, systems and methods, and that each of the figures isintended to accord with a possible embodiment thereof. Furthermore,wherever possible, the following description refers to the referencenumerals included in the following figures, in which features depictedin multiple figures are designated with consistent reference numerals.

FIG. 1 illustrates a block diagram of an exemplary computer network, acomputer server, a mobile device, and an on-board computer forimplementing autonomous vehicle operation, monitoring, evaluation, andinsurance processes in accordance with the described embodiments;

FIG. 2 illustrates a block diagram of an exemplary on-board computer ormobile device;

FIG. 3 illustrates a flow diagram of an exemplary autonomous vehicleoperation method in accordance with the presently described embodiments;

FIG. 4 illustrates a flow diagram of an exemplary monitoring methodduring vehicle operation in accordance with the presently describedembodiments;

FIG. 5 illustrates a flow diagram of an exemplary operating statusassessment method in accordance with the presently describedembodiments;

FIG. 6 illustrates a flow diagram of an exemplary operating statusmonitoring method in accordance with the presently describedembodiments;

FIGS. 7A-B illustrate flow diagrams depicting exemplary vehicleoperation hand-off methods in accordance with the presently describedembodiments;

FIG. 8 illustrates a flow diagram depicting an exemplary vehicleoperator identification method in accordance with the presentlydescribed embodiments;

FIG. 9 illustrates a flow diagram depicting an exemplary vehicleoperator use monitoring and evaluation method in accordance with thepresently described embodiments;

FIG. 10 illustrates a flow diagram depicting an exemplary costcomparison method in accordance with the presently describedembodiments; and

FIG. 11 illustrates a flow diagram depicting an exemplary autonomousoperation feature update method in accordance with the presentlydescribed embodiments;

FIG. 12 illustrates a flow diagram depicting an exemplary autonomousvehicle repair method in accordance with the presently describedembodiments; and

FIG. 13 illustrates a flow diagram depicting an exemplary infrastructurecommunication method in accordance with the presently describedembodiments.

DETAILED DESCRIPTION

The systems and methods disclosed herein generally relate to evaluating,monitoring, and managing risks related to the operation of autonomous orsemi-autonomous vehicles having autonomous (or semi-autonomous)operation features. The systems and methods further relate to pricingand processing vehicle insurance policies for autonomous orsemi-autonomous vehicles. The autonomous operation features may takefull control of the vehicle under certain conditions, viz. fullyautonomous operation, or the autonomous operation features may assistthe vehicle operator in operating the vehicle, viz. partially autonomousoperation. Fully autonomous operation features may include systemswithin the vehicle that pilot the vehicle to a destination with orwithout a vehicle operator present (e.g., an operating system for adriverless car). Partially autonomous operation features may assist thevehicle operator in limited ways (e.g., automatic braking or collisionavoidance systems).

The type and quality of the autonomous operation features may affect therisks related to operating a vehicle, both individually and/or incombination. In addition, configurations and settings of the autonomousoperation features may further impact the risks. To account for theeffects on such risks, some embodiments evaluate the quality of eachautonomous operation feature and/or combination of features. Additionalembodiments evaluate the risks associated with the vehicle operatorinteracting with the autonomous operation features. Further embodimentsaddress the relative risks associated with control of some aspects ofvehicle control by the autonomous operation features or by the vehicleoperator. Still further embodiments address use of information receivedor generated by the autonomous operation features to manage risk and/ordamage.

Some autonomous operation features may be adapted for use underparticular conditions, such as city driving or highway driving.Additionally, the vehicle operator may be able to configure settingsrelating to the features or may enable or disable the featuresindividually or in groups. For example, the vehicle operator may selecta mode of operation for the autonomous or semi-autonomous vehicle, whichmay adjust settings for one or more autonomous operation features.Therefore, some embodiments monitor use of the autonomous operationfeatures, which may include the settings or levels of feature use duringvehicle operation, as well as the selection of features or settings ofthe autonomous operation features chosen by the vehicle operator.

Information obtained by monitoring feature usage may be used todetermine risk levels associated with vehicle operation, eithergenerally or in relation to a vehicle operator. In such situations,total risk may be determined by a weighted combination of the risklevels associated with operation while autonomous operation features areenabled (with relevant settings) and the risk levels associated withoperation while autonomous operation features are disabled. For fullyautonomous vehicles, settings or configurations relating to vehicleoperation may be monitored and used in determining vehicle operatingrisk.

In addition to use in controlling the vehicle, information regarding therisks associated with vehicle operation with and without the autonomousoperation features may then be used to determine risk categories orpremiums for a vehicle insurance policy covering a vehicle withautonomous operation features. Risk category or price may be determinedbased upon factors relating to the evaluated effectiveness of theautonomous vehicle features. The risk or price determination may alsoinclude traditional factors, such as location, vehicle type, and levelof vehicle use. For fully autonomous vehicles, factors relating tovehicle operators may be excluded entirely. For partially autonomousvehicles, factors relating to vehicle operators may be reduced inproportion to the evaluated effectiveness and monitored usage levels ofthe autonomous operation features. For vehicles with autonomouscommunication features that obtain information from external sources(e.g., other vehicles or infrastructure), the risk level and/or pricedetermination may also include an assessment of the availability ofexternal sources of information. Location and/or tuning of vehicle usemay thus be monitored and/or weighted to determine the risk associatedwith operation of the vehicle.

Autonomous Automobile Insurance

The present embodiments may relate to assessing and pricing insurancebased upon autonomous (or semi-autonomous) functionality of a. vehicle,utilization of the autonomous semi-autonomous) functionality of thevehicle, and/or operation of the vehicle by a human operator. In someembodiments, the vehicle operator may not control the operations of thevehicle directly, in which case the assessment, rating, and pricing ofinsurance may exclude consideration of the vehicle operator. A smartvehicle may maneuver itself without human intervention and/or includesensors, processors, computer instructions, and/or other components thatmay perform or direct certain actions conventionally performed by ahuman operator.

An analysis of how artificial intelligence facilitates avoidingaccidents and/or mitigates the severity of accidents may be used tobuild a database and/or model of risk assessment. After which,automobile insurance risk and/or premiums (as well as insurancediscounts, rewards, and/or points) may be adjusted based upon autonomousor semi-autonomous vehicle functionality, such as by groups ofautonomous or semi-autonomous functionality or individual features. Inone aspect, an evaluation may be performed on how artificialintelligence, and the usage thereof, impacts automobile accidents and/orautomobile insurance claims.

The types of autonomous or semi-autonomous vehicle-related functionalityor technology that may be used with the present embodiments to replacehuman driver actions may include and/or be related to the followingtypes of functionality: (a) fully autonomous (driverless); (b) limiteddriver control; (c) vehicle-to-vehicle (V2V) wireless communication; (d)vehicle-to-infrastructure (and/or vice versa) wireless communication;(e) automatic or semi-automatic steering; (f) automatic orsemi-automatic acceleration; (g) automatic or semi-automatic braking;(h) automatic or semi-automatic blind spot monitoring; (i) automatic orsemi-automatic collision warning; (j) adaptive cruise control; (k)automatic or semi-automatic parking/parking assistance; (l) automatic orsemi-automatic collision preparation (windows roll up, seat adjustsupright, brakes pre-charge, etc.); (m) driver acuity/alertnessmonitoring; (n) pedestrian detection; (o) autonomous or semi-autonomousbackup systems; (p) road mapping systems; (q) software security andanti-hacking measures; (r) theft prevention/automatic return; (s)automatic or semi-automatic driving without occupants; and/or otherfunctionality. Additionally or alternatively, the autonomous orsemi-autonomous functionality or technology may include and/or may berelated to: (t) driver alertness or responsive monitoring; (u)pedestrian detection; (v) artificial intelligence and/or back-upsystems; (w) navigation or GPS-related systems; (x) security and/oranti-hacking measures; and/or (y) theft prevention systems.

The adjustments to automobile insurance rates or premiums based upon theautonomous or semi-autonomous vehicle-related functionality ortechnology may take into account the impact of such functionality ortechnology on the likelihood of a vehicle accident or collisionoccurring. For instance, a processor may analyze historical accidentinformation and/or test data involving vehicles having autonomous orsemi-autonomous functionality. Factors that may be analyzed and/oraccounted for that are related to insurance risk, accident information,or test data may include (1) point of impact; (2) type of road; (3) timeof day; (4) weather conditions; (5) road construction; (6) type/lengthof trip; (7) vehicle style; (8) level of pedestrian traffic; (9) levelof vehicle congestion; (10) atypical situations (such as manual trafficsignaling); (11) availability of internet connection for the vehicle;and/or other factors. These types of factors may also be weightedaccording to historical accident information, predicted accidents,vehicle trends, test data, and/or other considerations.

in one aspect, the benefit of one or more autonomous or semi-autonomousfunctionalities or capabilities may be determined, weighted, and/orotherwise characterized. For instance, the benefit of certain autonomousor semi-autonomous functionality may be substantially greater in city orcongested traffic, as compared to open road or country driving traffic.Additionally or alternatively, certain autonomous or semi-autonomousfunctionality may only work effectively below a certain speed, e.g.,during city driving or driving in congestion. Other autonomous orsemi-autonomous functionality may operate more effectively on thehighway and away from city traffic, such as cruise control. Furtherindividual autonomous or semi-autonomous functionality may be impactedby weather, such as rain or snow, and/or time of day (day light versusnight). As an example, fully automatic or semi-automatic lane detectionwarnings may be impacted by rain, snow, ice, and/or the amount ofsunlight (all of which may impact the imaging or visibility of lanemarkings painted onto a road surface, and/or road markers or streetsigns).

Automobile insurance premiums, rates, discounts, rewards, refunds,points, or other costs may be adjusted based upon the percentage of timeor vehicle usage that the vehicle is the driver, i.e., the amount oftime a specific driver uses each type of autonomous (or evensemi-autonomous) vehicle functionality. Such premiums, rates, discounts,rewards, refunds, points, or other costs may further be adjusted basedupon the extent of use of the autonomous operation features, includingsettings or modes impacting the operation of the autonomous operationfeatures. Moreover, information regarding the vehicle environment duringuse (e.g., weather, traffic, time of day, etc.) may be included ininsurance adjustment determinations, as may traditional informationregarding one or more vehicle operators (and the extent to which eachvehicle operator uses the vehicle).

Such usage information for a particular vehicle may be gathered overtime and/or via remote wireless communication with the vehicle. Oneembodiment may involve a processor on the vehicle, such as within avehicle control system or dashboard, monitoring in real-time the vehicleoperator and/or the use of autonomous operation features while thevehicle is operating. Other types of monitoring may be remotelyperformed, such as via wireless communication between the vehicle and aremote server, or wireless communication between a vehicle-mounteddedicated device (that is configured to gather autonomous orsemi-autonomous functionality usage information) and a remote server.

Additionally, in some embodiments, the vehicle may transmit and/orreceive communications to or from external sources, such as othervehicles (V2V), infrastructure (e.g., a bridge, traffic light, railroadcrossing, toll both, marker, sign, or other equipment along the side ofa road or highway), pedestrians, databases, or other information sourcesexternal to the vehicle. Such communication may allow the vehicle toobtain information regarding other vehicles, obstacles, road conditions,or environmental conditions that could not be detected by sensorsdisposed within the vehicle. For example, V2V communication may allow avehicle to identify other vehicles approaching an intersection even whenthe direct line between the vehicle and the other vehicles is obscuredby buildings. As another example, the V2V wireless communication from afirst vehicle to a second vehicle (following the first vehicle) mayindicate that the first vehicle is braking, which may include the degreeto which the vehicle is braking. In response, the second vehicle mayautomatically or autonomously brake in advance of detecting thedeceleration of the first vehicle based upon sensor data.

Insurance premiums, rates, ratings, discounts, rewards, special offers,points, programs, refunds, claims, claim amounts, or other costsassociated with an insurance policy may be adjusted for, or mayotherwise take into account, the foregoing functionality and/or theother functionality described herein. For instance, insurance policiesmay be updated based upon installed autonomous operation features, theextent of use of the autonomous operation features, V2V wirelesscommunication, and/or vehicle-to-infrastructure orinfrastructure-to-vehicle wireless communication. The presentembodiments may assess and price insurance risks at least in part basedupon autonomous operation features that replace some actions of thevehicle operator in controlling the vehicle, including settings andoperating status of the autonomous operation features.

Exemplary Autonomous Vehicle Operation System

FIG. 1 illustrates a block diagram of an exemplary autonomous vehicleinsurance system 100 on which the exemplary methods described herein maybe implemented. The high-level architecture includes both hardware andsoftware applications, as well as various data communications channelsfor communicating data between the various hardware and softwarecomponents. The autonomous vehicle insurance system 100 may be roughlydivided into front-end components 102 and back-end components 104. Thefront-end components 102 may obtain information regarding a vehicle 108(e.g., a car, truck, motorcycle, etc.) and the surrounding environment.An on-board computer 114 may utilize this information to operate thevehicle 108 according to an autonomous operation feature or to assistthe vehicle operator in operating the vehicle 108. To monitor thevehicle 108, the front-end components 102 may include one or moresensors 120 installed within the vehicle 108 that may communicate withthe on-board computer 114. The front-end components 102 may furtherprocess the sensor data using the on-board computer 114 or a mobiledevice 110 (e.g., a smart phone, a tablet computer, a special purposecomputing device, etc.) to determine when the vehicle is in operationand information regarding the vehicle. In some embodiments of the system100, the front-end components 102 may communicate with the back-endcomponents 104 via a network 130. Either the on-board computer 114 orthe mobile device 110 may communicate with the back-end components 104via the network 130 to allow the back-end components 104 to recordinformation regarding vehicle usage. The back-end components 104 may useone or more servers 140 to receive data from the front-end components102, determine use and effectiveness of autonomous operation features,determine risk levels or premium price, and/or facilitate purchase orrenewal of an autonomous vehicle insurance policy.

The front-end components 102 may be disposed within or communicativelyconnected to one or more on-board computers 114, which may bepermanently or removably installed in the vehicle 108. The on-boardcomputer 114 may interface with the one or more sensors 120 within thevehicle 108 (e.g., an ignition sensor, an odometer, a system clock, aspeedometer, a tachometer, an accelerometer, a gyroscope, a compass, ageolocation unit, a camera, a distance sensor, etc.), which sensors mayalso be incorporated within or connected to the on-board computer 114.The front-end components 102 may further include a communicationcomponent 122 to transmit information to and receive information fromexternal sources, including other vehicles, infrastructure, or theback-end components 104, in some embodiments, the mobile device 110 maysupplement the functions performed by the on-board computer 114described herein by, for example, sending or receiving information toand from the mobile server 140 via the network 130. In otherembodiments, the on-board computer 114 may perform all of the functionsof the mobile device 110 described herein, in which case no mobiledevice 110 may be present in the system 100. Either or both of themobile device 110 or on-board computer 114 may communicate with thenetwork 130 over links 112 and 118, respectively. Additionally, themobile device 110 and on-board computer 114 may communicate with oneanother directly over link 116.

The mobile device 110 may be either a general-use personal computer,cellular phone, smart phone, tablet computer, phablet, wearableelectronics, PDA (personal digital assistant), smart glasses, smartwatches, smart bracelet, pager, computing device configured for wired orwireless RF (radio frequency) communication, a dedicated vehicle usemonitoring device, and/or other mobile computing device. Although onlyone mobile device 110 is illustrated, it should be understood that aplurality of mobile devices 110 may be used in some embodiments. Theon-board computer 114 may be a general-use on-board computer capable ofperforming many functions relating to vehicle operation or a dedicatedcomputer for autonomous vehicle operation. Further, the on-boardcomputer 114 may be installed by the manufacturer of the vehicle 108 oras an aftermarket modification or addition to the vehicle 108, In someembodiments or under certain conditions, the mobile device 110 oron-board computer 114 may function as thin-client devices that outsourcesome or most of the processing to the server 140.

The sensors 120 may be removably or fixedly installed within the vehicle108 and may be disposed in various arrangements to provide informationto the autonomous operation features. Among the sensors 120 may beincluded one or more of a GPS (Global Positioning System) unit, othersatellite-based navigation unit, a radar unit, a LIDAR (Light Detectionand Ranging) unit, an ultrasonic sensor, an infrared sensor, a camera,an accelerometer, a tachometer, and/or a speedometer. Some of thesensors 120 (e.g., radar, LIDAR, or camera units) may actively orpassively scan the vehicle environment for obstacles (e.g., othervehicles, buildings, pedestrians, etc.), lane markings, or signs orsignals. Other sensors 120 (e.g., GPS. accelerometer, or tachometerunits) may provide data for determining the location or movement of thevehicle 108. Other sensors 120 may be directed to the interior orpassenger compartment of the vehicle 108, such as cameras, microphones,pressure sensors, thermometers, or similar sensors to monitor thevehicle operator and/or passengers within the vehicle 108. Informationgenerated or received by the sensors 120 may be communicated to theon-board computer 114 or the mobile device 110 for use in autonomousvehicle operation.

in some embodiments, the communication component 122 may receiveinformation from external sources, such as other vehicles orinfrastructure. The communication component 122 may also sendinformation regarding the vehicle 108 to external sources. To send andreceive information, the communication component 122 may include atransmitter and a receiver designed to operate according topredetermined specifications, such as the dedicated short-rangecommunication (DSRC) channel, wireless telephony, Wi-Fi, or otherexisting or later-developed communications protocols. The receivedinformation may supplement the data received from the sensors 120 toimplement the autonomous operation features. For example, thecommunication component 122 may receive information that an autonomousvehicle ahead of the vehicle 108 is reducing speed, allowing theadjustments in the autonomous operation of the vehicle 108.

In further embodiments, the front-end components may include aninfrastructure communication device 124 for monitoring the status of oneor more infrastructure components 126. The infrastructure communicationdevice 124 may include or be communicatively connected to one or moresensors (not shown) for detecting information relating to the conditionof the infrastructure component 126. The sensors (not shown) maygenerate data relating to weather conditions, traffic conditions, oroperating status of the infrastructure component 126. The infrastructurecommunication device 124 may be configured to receive the sensor datagenerated and determine a condition of the infrastructure component 126,such as weather conditions, road integrity, construction, traffic,available parking spaces, etc. The infrastructure communication device124 may further be configured to communicate information to vehicles 108via the communication component 122. In some embodiments, theinfrastructure communication device 124 may receive information from thevehicles 108, while, in other embodiments, the infrastructurecommunication device 124 may only transmit information to the vehicles108.

In addition to receiving information from the sensors 120, the on-boardcomputer 114 may directly or indirectly control the operation of thevehicle 108 according to various autonomous operation features. Theautonomous operation features may include software applications orroutines implemented by the on-board computer 114 to control thesteering, braking, or throttle of the vehicle 108. To facilitate suchcontrol, the on-board computer 114 may be communicatively connected tothe controls or components of the vehicle 108 by various electrical orelectromechanical control components (not shown). In embodimentsinvolving fully autonomous vehicles, the vehicle 108 may be operableonly through such control components (not shown). In other embodiments,the control components may be disposed within or supplement othervehicle operator control components (not shown), such as steeringwheels, accelerator or brake pedals, or ignition switches.

in some embodiments, the front-end components 102 may communicate withthe back-end components 104 via the network 130. The network 130 may bea proprietary network, a secure public internet, a virtual privatenetwork or some other type of network, such as dedicated access lines,plain ordinary telephone lines, satellite links, cellular data networks,combinations of these. Where the network 130 comprises the Internet,data communications may take place over the network 130 via an Internetcommunication protocol.

The back-end components 104 may include one or more servers 140, Eachserver 140 may include one or more computer processors adapted andconfigured to execute various software applications and components ofthe autonomous vehicle insurance system 100, in addition to othersoftware applications. The server 140 may further include a database146, which may be adapted to store data related to the operation of thevehicle 108 and its autonomous operation features. Such data mightinclude, for example, dates and times of vehicle use, duration ofvehicle use, use and settings of autonomous operation features, speed ofthe vehicle 108, RPM or other tachometer readings of the vehicle 108,lateral and longitudinal acceleration of the vehicle 108, incidents ornear collisions of the vehicle 108, communication between the autonomousoperation features and external sources, environmental conditions ofvehicle operation (e.g., weather, traffic, road condition, etc.), errorsor failures of autonomous operation features, or other data relating touse of the vehicle 108 and the autonomous operation features, which maybe uploaded to the server 140 via the network 130. The server 140 mayaccess data stored in the database 146 when executing various functionsand tasks associated with the evaluating feature effectiveness orassessing risk relating to an autonomous vehicle.

Although the autonomous vehicle insurance system 100 is shown to includeone vehicle 108, one mobile device 110, one on-board computer 114, andone server 140, it should be understood that different numbers ofvehicles 108, mobile devices 110, on-board computers 114, and/or servers140 may be utilized. For example, the system 100 may include a pluralityof servers 140 and hundreds of mobile devices 110 or on-board computers114, all of which may be interconnected via the network 130.Furthermore, the database storage or processing performed by the one ormore servers 140 may be distributed among a plurality of servers 140 inan arrangement known as “cloud computing.” This configuration mayprovide various advantages, such as enabling near real-time uploads anddownloads of information as well as periodic uploads and downloads ofinformation. This may in turn support a thin-client embodiment of themobile device 110 or on-board computer 114 discussed herein.

The server 140 may have a controller 155 that is operatively connectedto the database 146 via a link 156. It should be noted that, while notshown, additional databases may be linked to the controller 155 in aknown manner. For example, separate databases may be used for autonomousoperation feature information, vehicle insurance policy information, andvehicle use information. The controller 155 may include a program memory160, a processor 162 (which may be called a microcontroller or amicroprocessor), a random-access memory (RAM) 164, and an input/output(I/O) circuit 166, all of which may be interconnected via anaddress/data bus 165. It should be appreciated that although only onemicroprocessor 162 is shown, the controller 155 may include multiplemicroprocessors 162. Similarly, the memory of the controller 155 mayinclude multiple RAMs 164 and multiple program memories 160. Althoughthe I/O circuit 166 is shown as a single block, it should be appreciatedthat the I/O circuit 166 may include a number of different types of I/Ocircuits. The RAM 164 and program memories 160 may be implemented assemiconductor memories, magnetically readable memories, or opticallyreadable memories, for example. The controller 155 may also beoperatively connected to the network 130 via a link 135.

The server 140 may further include a number of software applicationsstored in a program memory 160. The various software applications on theserver 140 may include an autonomous operation information monitoringapplication 141 for receiving information regarding the vehicle 108 andits autonomous operation features, a feature evaluation application 142for determining the effectiveness of autonomous operation features undervarious conditions, a compatibility evaluation application 143 fordetermining the effectiveness of combinations of autonomous operationfeatures, a risk assessment application 144 for determining a riskcategory associated with an insurance policy covering an autonomousvehicle, and an autonomous vehicle insurance policy purchase application145 for offering and facilitating purchase or renewal of an insurancepolicy covering an autonomous vehicle. The various software applicationsmay be executed on the same computer processor or on different computerprocessors.

The various software applications may include various software routinesstored in the program memory 160 to implement various modules using theprocess 162. Additionally, or alternatively, the software applicationsor routines may interact with various hardware modules that may beinstalled within or connected to the server 140. Such modules mayimplement part of all of the various exemplary methods discussed hereinor other related embodiments. Such modules may include a vehicle controlmodule for determining and implementing control decisions to operate thevehicle 108, a system status module for determining the operating statusof autonomous operation features, a monitoring module for monitoring theoperation of the vehicle 108, a remediation module for correctingabnormal operating states of autonomous operation features, an insurancemodule for determining risks and costs associated with operation of thevehicle 108, an alert module for generating and presenting alertsregarding the vehicle 108 or the vehicle operator, a risk assessmentmodule for determining risks associated with operation of the vehicle108 by the autonomous operation features or by the vehicle operator, anidentification module for identifying or verifying the identity of thevehicle operator, an information module for obtaining informationregarding a vehicle operator or vehicle 108, a use cost module fordetermining costs associated with operation of the vehicle 108, acomparison module for comparing one or more costs associated with owningor operating the vehicle 108, an update module for updating anautonomous operation feature of the vehicle 108, or other modules.

Exemplary Mobile Device or On-Board Computer

FIG. 2 illustrates a block diagram of an exemplary mobile device 110and/or an exemplary on-board computer 114 consistent with the system100. The mobile device 110 and/or on-board computer 114 may include adisplay 202, a GPS unit 206, a communication unit 220, an accelerometer224, one or more additional sensors (not shown), a user-input device(not shown), and/or, like the server 140, a controller 204. In someembodiments, the mobile device 110 and on-board computer 114 may beintegrated into a single device, or either may perform the functions ofboth. The on-board computer 114 (or mobile device 110) may interfacewith the sensors 120 to receive information regarding the vehicle 108and its environment, which information may be used by the autonomousoperation features to operate the vehicle 108.

Similar to the controller 155, the controller 204 may include a programmemory 208, one or more microcontrollers or microprocessors (MP) 210, aRAM 212, and an I/O circuit 216, all of which are interconnected via anaddress/data bus 214. The program memory 208 may include an operatingsystem 226, a data storage 228, a plurality of software applications230, and/or a plurality of software routines 240. The operating system226, for example, may include one of a plurality of general purpose ormobile platforms, such as the Android™, iOS®, or Windows® systems,developed by Google Inc., Apple Inc., and Microsoft Corporation,respectively. Alternatively, the operating system 226 may be a customoperating system designed for autonomous vehicle operation using theon-board computer 114. The data storage 228 may include data such asuser profiles and preferences, application data for the plurality ofapplications 230, routine data for the plurality of routines 240, andother data related to the autonomous operation features. In someembodiments, the controller 204 may also include, or otherwise becommunicatively connected to, other data storage mechanisms (e.g., oneor more hard disk drives, optical storage drives, solid state storagedevices, etc.) that reside within the vehicle 108.

As discussed with reference to the controller 155, it should beappreciated that although FIG. 2 depicts only one microprocessor 210,the controller 204 may include multiple microprocessors 210. Similarly,the memory of the controller 204 may include multiple RAMs 212 andmultiple program memories 208. Although FIG. 2 depicts the 110 circuit216 as a single block, the I/O circuit 216 may include a number ofdifferent types of I/O circuits. The controller 204 may implement theRAMs 212 and the program memories 208 as semiconductor memories,magnetically readable memories, or optically readable memories, forexample.

The one or more processors 210 may be adapted and configured to executeany of one or more of the plurality of software applications 230 or anyone or more of the plurality of software routines 240 residing in theprogram memory 204, in addition to other software applications. One ofthe plurality of applications 230 may be an autonomous vehicle operationapplication 232 that may be implemented as a series of machine-readableinstructions for performing the various tasks associated withimplementing one or more of the autonomous operation features accordingto the autonomous vehicle operation method 300. Another of the pluralityof applications 230 may be an autonomous communication application 234that may be implemented as a series of machine-readable instructions fortransmitting and receiving autonomous operation information to or fromexternal sources via the communication unit 220. Still anotherapplication of the plurality of applications 230 may include anautonomous operation monitoring application 236 that may be implementedas a series of machine-readable instructions for sending informationregarding autonomous operation of the vehicle to the server 140 via thenetwork 130.

The plurality of software applications 230 may call various of theplurality of software routines 240 to perform functions relating toautonomous vehicle operation, monitoring, or communication. In someembodiments, the plurality of software routines may further assess risklevels or determine insurance policy costs and adjustments. One of theplurality of software routines 240 may be a configuration routine 242 toreceive settings from the vehicle operator to configure the operatingparameters of an autonomous operation feature. Another of the pluralityof software routines 240 may be a sensor control routine 244 to transmitinstructions to a sensor 120 and receive data from the sensor 120. Stillanother of the plurality of software routines 240 may be an autonomouscontrol routine 246 that performs a type of autonomous control, such ascollision avoidance, lane centering, and/or speed control. In someembodiments, the autonomous vehicle operation application 232 may causea plurality of autonomous control routines 246 to determine controlactions required for autonomous vehicle operation. Similarly, one of theplurality of software routines 240 may be a monitoring and reportingroutine 248 that monitors and transmits information regarding autonomousvehicle operation to the server 140 via the network 130. Yet another ofthe plurality of software routines 240 may be an autonomouscommunication routine 250 for receiving and transmitting informationbetween the vehicle 108 and external sources to improve theeffectiveness of the autonomous operation features.

Any of the plurality of software routines 240 may be designed to operateindependently of the software applications 230 or in conjunction withthe software applications 230 to implement modules associated with themethods discussed herein using the microprocessor 210 of the controller204. Additionally, or alternatively, the software applications 230 orsoftware routines 240 may interact with various hardware modules thatmay be installed within or connected to the mobile device 110 or theon-board computer 114. Such modules may implement part of all of thevarious exemplary methods discussed herein or other related embodiments.

For instance, such modules may include a vehicle control module fordetermining and implementing control decisions to operate the vehicle108, a system status module for determining the operating status ofautonomous operation features, a monitoring module for monitoring theoperation of the vehicle 108, a remediation module for correctingabnormal operating states of autonomous operation features, an insurancemodule for determining risks and costs associated with operation of thevehicle 108, an alert module for generating and presenting alertsregarding the vehicle 108 or the vehicle operator, a risk assessmentmodule for determining risks associated with operation of the vehicle108 by the autonomous operation features or by the vehicle operator, anidentification module for identifying or verifying the identity of thevehicle operator, an information module for obtaining informationregarding a vehicle operator or vehicle 108, a use cost module fordetermining costs associated with operation of the vehicle 108, acomparison module for comparing one or more costs associated with owningor operating the vehicle 108, an update module for updating anautonomous operation feature of the vehicle 108. and/or other modules.

When implementing the exemplary autonomous vehicle operation method 300,the controller 204 of the on-board computer 114 may implement a vehiclecontrol module by the autonomous vehicle operation application 232 tocommunicate with the sensors 120 to receive information regarding thevehicle 108 and its environment and process that information forautonomous operation of the vehicle 108. In some embodiments, includingexternal source communication via, the communication component 122 orthe communication unit 220, the controller 204 may further implement acommunication module based upon the autonomous communication application234 to receive information for external sources, such as otherautonomous vehicles, smart infrastructure (e.g., electronicallycommunicating roadways, traffic signals, or parking structures), orother sources of relevant information (e.g., weather, traffic, localamenities). Some external sources of information may be connected to thecontroller 204 via the network 130, such as the server 140 orinternet-connected third-party databases (not shown). Although theautonomous vehicle operation application 232 and the autonomouscommunication application 234 are shown as two separate applications, itshould be understood that the functions of the autonomous operationfeatures may be combined or separated into any number of the softwareapplications 230 or the software routines 240.

In some embodiments, the controller 204 may further implement amonitoring module by the autonomous operation monitoring application 236to communicate with the server 140 to provide information regardingautonomous vehicle operation. This may include information regardingsettings or configurations of autonomous operation features, data fromthe sensors 120 regarding the vehicle environment, data from the sensors120 regarding the response of the vehicle 108 to its environment,communications sent or received using the communication component 122 orthe communication unit 220, operating status of the autonomous vehicleoperation application 232 and the autonomous communication application234, and/or commands sent from the on-board computer 114 to the controlcomponents (not shown) to operate the vehicle 108. The information maybe received and stored by the server 140 implementing the autonomousoperation information monitoring application 141, and the server 140 maythen determine the effectiveness of autonomous operation under variousconditions by implementing the feature evaluation application 142 andthe compatibility evaluation application 143. The effectiveness ofautonomous operation features and the extent of their use may be furtherused to determine risk associated with operation of the autonomousvehicle by the server 140 implementing a risk assessment module orinsurance module associated with the risk assessment application 144.

In addition to connections to the sensors 120, the mobile device 110 orthe on-board computer 114 may include additional sensors, such as theGPS unit 206 or the accelerometer 224, which may provide informationregarding the vehicle 108 for autonomous operation and other purposes.Furthermore, the communication unit 220 may communicate with otherautonomous vehicles, infrastructure, or other external sources ofinformation to transmit and receive information relating to autonomousvehicle operation. The communication unit 220 may communicate with theexternal sources via the network 130 or via any suitable wirelesscommunication protocol network, such as wireless telephony (e.g., GSM,CDMA, LIE, etc.), Wi-Fi (802.11 standards), WiMAX, Bluetooth, infraredor radio frequency communication, etc. Furthermore, the communicationunit 220 may provide input signals to the controller 204 via the I/Ocircuit 216. The communication unit 220 may also transmit sensor data,device status information, control signals, and/or other output from thecontroller 204 to one or more external sensors within the vehicle 108,mobile devices 110, on-board computers 114, and/or servers 140.

The mobile device 110 and/or the on-board computer 114 may include auser-input device (not shown) for receiving instructions or informationfrom the vehicle operator, such as settings relating to an autonomousoperation feature. The user-input device (not shown) may include a“soft” keyboard that is displayed on the display 202, an externalhardware keyboard communicating via a wired or a wireless connection(e.g., a Bluetooth keyboard), an external mouse, a microphone, or anyother suitable user-input device. The user-input device (not shown) mayalso include a microphone capable of receiving user voice input.

Exemplary Autonomous Vehicle Operation Method

FIG. 3 illustrates a flow diagram of an exemplary autonomous vehicleoperation method 300, which may be implemented by the autonomous vehicleinsurance system 100. The method 300 may begin at block 302 when thecontroller 204 receives a start signal. The start signal may be acommand from the vehicle operator through the user-input device toenable or engage one or more autonomous operation features of thevehicle 108. In some embodiments, the vehicle operator 108 may furtherspecify settings or configuration details for the autonomous operationfeatures. For fully autonomous vehicles, the settings may relate to oneor more destinations, route preferences, fuel efficiency preferences,speed preferences, and/or other configurable settings relating to theoperation of the vehicle 108. In some embodiments, fully autonomousvehicles may include additional features or settings permitting them tooperate without passengers or vehicle operators within the vehicle. Forexample, a fully autonomous vehicle may receive an instruction to find aparking space within the general vicinity, which the vehicle may dowithout the vehicle operator, The vehicle may then be returned to aselected location by a request from the vehicle operator via a mobiledevice 110 or otherwise. This feature may further be adapted to return afully autonomous vehicle if lost or stolen.

For other autonomous vehicles, the settings may include enabling ordisabling particular autonomous operation features, specifyingthresholds for autonomous operation, specifying warnings or otherinformation to be presented to the vehicle operator, specifyingautonomous communication types to send or receive, specifying conditionsunder which to enable or disable autonomous operation features, and/orspecifying other constraints on feature operation. For example, avehicle operator may set the maximum speed for an adaptive cruisecontrol feature with automatic lane centering. In some embodiments, thesettings may further include a specification of whether the vehicle 108should be operating as a fully or partially autonomous vehicle. Inembodiments where only one autonomous operation feature is enabled, thestart signal may consist of a request to perform a particular task(e.g., autonomous parking) and/or to enable a particular feature (e.g.,autonomous braking for collision avoidance). In other embodiments, thestart signal may be generated automatically by the controller 204 basedupon predetermined settings (e.g., when the vehicle 108 exceeds acertain speed and/or is operating in low-light conditions). In someembodiments, the controller 204 may generate a start signal whencommunication from an external source is received (e.., when the vehicle108 is on a smart highway or near another autonomous vehicle).

After receiving the start signal at block 302, the controller 204 mayreceive sensor data from the sensors 120 during vehicle operation atblock 304. In some embodiments, the controller 204 may also receiveinformation from external sources through the communication component122 and/or the communication unit 220. The sensor data may be stored inthe RAM 212 for use by the autonomous vehicle operation application 232.In some embodiments, the sensor data may be recorded in the data storage228 and/or transmitted to the server 140 via the network 130, The sensordata may alternately either be received by the controller 204 as rawdata measurements from one of the sensors 120 and/or may be preprocessedby the sensor 120 prior to being received by the controller 204. Forexample, a tachometer reading may be received as raw data and/or may bepreprocessed to indicate vehicle movement or position. As anotherexample, a sensor 120 comprising a radar and/or LIDAR unit may include aprocessor to preprocess the measured signals and send data representingdetected objects in 3-dimensional space to the controller 204.

The autonomous vehicle operation application 232, other applications230, and/or routines 240 may cause the controller 204 to process thereceived sensor data at block 306 in accordance with the autonomousoperation features. The controller 204 may process the sensor data todetermine whether an autonomous control action is required and/or todetermine adjustments to the controls of the vehicle 108. For example,the controller 204 may receive sensor data indicating a decreasingdistance to a nearby object in the vehicle's path and process thereceived sensor data to determine whether to begin braking (and, if so,how abruptly to slow the vehicle 108). As another example, thecontroller 204 may process the sensor data to determine whether thevehicle 108 is remaining with its intended path (e.g., within lanes on aroadway). If the vehicle 108 is beginning to drift or slide (e.g., as onice or water), the controller 204 may determine appropriate adjustmentsto the controls of the vehicle to maintain the desired bearing. If thevehicle 108 is moving within the desired path, the controller 204 maynonetheless determine whether adjustments are required to continuefollowing the desired route following a winding road). Under someconditions, the controller 204 may determine to maintain the controlsbased upon the sensor data (e.g., when holding a steady speed on astraight road).

When the controller 204 determines an autonomous control action isrequired at block 308, the controller 204 may cause the controlcomponents of the vehicle 108 to adjust the operating controls of thevehicle to achieve desired operation at block 310. For example, thecontroller 204 may send a signal to open or close the throttle of thevehicle 108 to achieve a desired speed. Alternatively, the controller204 may control the steering of the vehicle 108 to adjust the directionof movement. In some embodiments, the vehicle 108 may transmit a messageor indication of a change in velocity or position using thecommunication component 122 and/or the communication unit 220, whichsignal may be used by other autonomous vehicles to adjust theircontrols. As discussed further below, the controller 204 may also log ortransmit the autonomous control actions to the server 140 via thenetwork 130 for analysis.

The controller 204 may continue to receive and process sensor data atblocks 304 and 306 until an end signal is received by the controller 204at block 312. The end signal may be automatically generated by thecontroller 204 upon the occurrence of certain criteria (e.g., thedestination is reached or environmental conditions require manualoperation of the vehicle 108 by the vehicle operator). Additionally, oralternatively, the vehicle operator may pause, terminate, and/or disablethe autonomous operation feature or features using the user-input deviceor by manually operating the vehicle's controls, such as by depressing apedal or turning. a steering instrument. When the autonomous operationfeatures are disabled or terminated, the controller 204 may eithercontinue vehicle operation without the autonomous features or may shutoff the vehicle 108, depending upon the circumstances.

Where control of the vehicle 108 must be returned to the vehicleoperator, the controller 204 may alert the vehicle operator in advanceof returning to manual operation. The alert may include a visual, audio,and/or other indication to obtain the attention of the vehicle operator.In some embodiments, the controller 204 may further determine whetherthe vehicle operator is capable of resuming manual operation beforeterminating autonomous operation. If the vehicle operator is determinednot be capable of resuming operation, the controller 204 may cause thevehicle to stop and/or take other appropriate action.

Exemplary Monitoring Method During Operation

FIG. 4 illustrates a flow diagram depicting an exemplary monitoringmethod 400 during vehicle operation, which may be implemented by theautonomous vehicle insurance system 100. The method 400 may monitor theoperation of the vehicle 108 and adjust risk levels and rates based uponvehicle use. Although the exemplary embodiment is described as primarilyperformed by the on-board computer 114, the method 400 may beimplemented by the mobile device 110, the on-board computer 114, theserver 140, or a combination thereof Upon receiving an indication ofvehicle operation at block 402, the on-board computer 114 may determinethe configuration and operating status of the autonomous operationfeatures (including the sensors 120 and the communication component 122)at block 404. The identity of the vehicle operator may be determinedand/or verified at block 406, which identity may be used to determine orreceive a vehicle operator profile at block 408. The vehicle operatorprofile may contain information regarding the vehicle operator's abilityto manually operate the vehicle and/or past use of autonomous operationfeatures by the vehicle operator. Information from the sensors 120and/or external data from the communication component 122 may be used atblock 410 to determine environmental conditions in which the vehicle 108is operating. Together, this information determined at blocks 404-410may be used at block 412 to determine one or more risk levels associatedwith operation of the vehicle, from which may be determined a costsassociated with an insurance policy at block 414. In some embodiments,information regarding the determined cost may be presented to thevehicle operator or other insurance customer associated with the vehicle108 at block 416. In still further embodiments, the vehicle operatorand/or insurance customer may be presented with recommendations oroptions regarding the cost associated with the insurance policy at block418. Presentation of options may assist the vehicle operator and/orinsurance customer in reducing the cost by allowing the vehicle operatorand/or insurance customer to select a lower-cost option (e.g., byadjusting the settings associated with the autonomous operationfeatures). In some embodiments, the vehicle operator and/or insurancecustomer may be able to select one or more of the options to effect anadjustment in the risk levels and/or insurance cost.

The method 400 may continue monitoring operation of the vehicle 108 atblock 420, and adjustments may be made to the risk levels and insurancecosts. If the settings associated with the autonomous operation featuresare determined to have changed at block 422 (e.g., as a result of thevehicle operator taking manual operation of additional controls), theone or more risk levels may be determined based upon the new settings atblock 412, in which case the blocks 414-422 may be repeated. When nochanges have been made to the settings, the method 400 may further checkfor changes to the environmental conditions and/or operating status ofthe autonomous operation features at block 424. If changes aredetermined to have occurred at block 424, the one or more risk levelsmay be determined based upon the new settings at block 412, as at block422. When no changes have occurred, the method 400 may determine whethervehicle operations are ongoing or whether operation is complete at block426. When vehicle operation is ongoing, the method 400 may continue tomonitor vehicle operation at block 420. When vehicle operation iscomplete, information regarding operation of the vehicle may be recordedat block 428, at which point the method 400 may terminate.

At block 402, the on-board computer 114 may receive an indication ofvehicle operation. This indication may be received from the vehicleoperator (either directly or through the mobile device 110), and/or itmay be generated automatically. For example, the on-board computer 114or the mobile device 110 may automatically generate an indication ofvehicle operation when the vehicle starts operation (e.g., upon engineignition, system power-up, movement of the vehicle 108, etc.), Uponreceiving the indication of vehicle operation, the on-board computer 114may initiate a system check and/or begin recording information regardingoperation of the vehicle 108.

At block 404, the on-board computer 114 may determine the configurationand operating status of one or more autonomous operation features of thevehicle 108. This may include determining the configuration, settings,and/or operating status of one or more hardware or software modules forcontrolling part or all of the vehicle operation, aftermarket componentsdisposed within the vehicle to provide information regarding vehicleoperation, and/or sensors 120 disposed within the vehicle. In someembodiments, a software version, model version, and/or otheridentification of the feature or sensor may be determined, In furtherembodiments, the autonomous operation feature may be tested to assessproper functioning, which may be accomplished using a test routine orother means. Additionally, the sensors 120 or the communicationcomponent 122 may be assessed to determine their operating status (e.g.,quality of communication connections, signal quality, noise,responsiveness, accuracy. etc.). In some embodiments, test signals maybe sent to one or more of the sensors 120, responses to which may bereceived and/or assessed by the on-board computer to determine operatingstatus. In further embodiments, signals received from a plurality ofsensors may be compared to determine whether any of the sensors aremalfunctioning. Additionally, signals received from the sensors may beused, in some embodiments, to calibrate the sensors.

At block 406, the on-board computer 114 may determine the identity ofthe vehicle operator. To determine the identity of the vehicle operator,the on-board computer 114 may receive and process information regardingthe vehicle operator. In some embodiments, the received information mayinclude sensor data from one or more sensors 120 configured to monitorthe interior of the vehicle. For example, a camera or other photographicsensor may provide photographic information regarding the vehicleoperator, which may be processed and compared with other photographicdata for a plurality of persons to determine the identity of the vehicleoperator. In further embodiments, the on-board computer may receiveinformation from a mobile computing device associated with the vehicleoperator, such as a mobile phone or wearable computing device. Forexample, a mobile phone may connect to the on-board computer 114, whichmay identify the vehicle operator. Additional steps may be taken toverify the identity of the vehicle operator, such as comparing a weightsensed on a seat or use of voice recognition algorithms.

At block 408, the on-board computer 114 may determine and/or access avehicle operator profile based upon the identity of the vehicle operatordetermined at block 406. The vehicle operator profile may includeinformation regarding the vehicle operator's style of operating thevehicle, including information regarding past operation of one or morevehicles by the vehicle operator. This information may further containpast vehicle operator selections of settings for one or more autonomousoperation features. In some embodiments, the on-board computer 114 mayrequest or access the vehicle operator profiled based upon thedetermined identity. In other embodiments, the on-board computer 114 maygenerate the vehicle operator profile from information associated withthe identified vehicle operator. The vehicle operator profile mayinclude information relating to one or more risks associated withoperation of the vehicle by the vehicle operator. For example, thevehicle operator profile for a driver may include information relatingto risk levels based upon past driving patters or habits in a variety ofrelevant environments, which may include risk levels associated withmanual operation of the vehicle by the driver. In some embodiments, thevehicle operator profile may include information regarding defaultsettings used by the vehicle operator for the autonomous operationfeatures.

At block 410, the on-board computer 114 may determine environmentalconditions within which the vehicle 108 is or is likely to be operating.Such environmental conditions may include weather, traffic, roadconditions, time of day, location of operation, type of road, and/orother information relevant to operation of the vehicle. Theenvironmental conditions may be determined based upon signals receivedfrom the sensors 120, from external data received through thecommunication component 122, and/or from a combination of sources. Theenvironmental conditions may then be used in determining risk levelsassociated with operation of the vehicle 108.

At block 412, the on-board computer may determine one or more risklevels associated with operation of the vehicle 108. The risk levels maybe determined based upon a combination of risk factors relating to theautonomous operation features and/or risk factors relating to thevehicle operation. Risks associated with the autonomous operationfeatures may be determined based upon the configuration and/or operatingstatus of the autonomous operation features, the settings of theautonomous operation features, and the vehicle environment. Risksassociated with the vehicle operation may be determined based upon theautonomous operation features settings (i.e., the extent to which thevehicle operator will be controlling vehicle operations) and/or thevehicle operator profile. The combined risk may account for thelikelihood of the autonomous operation features and/or the vehicleoperator controlling vehicle operations with respect to relevantfunctions of the vehicle 108.

At block 414, the on-board computer 114 may determine a cost associatedwith an insurance policy based upon the one or more risks. In someembodiments, the server 140 may receive information regarding thevehicle operator and the autonomous operation features and/or maydetermine the cost associated with the insurance policy based upon therisks, The cost may be based upon risk levels associated with separateautonomous operation features, interaction between autonomous operationfeatures, the design and capabilities of the vehicle 108, the pastoperating history of the vehicle operator as included in the vehicleoperator profile, and/or other information regarding the probability ofan accident, collision, and/or other loss event involving the vehicle108. Each of the separate risks may depend upon the environmentalconditions, and the risks may be weighted based upon the likelihood ofeach situation. In some embodiments, a total risk may be determinedrelating to operation of the vehicle under foreseeable conditions withspecific settings and configurations of autonomous operation features bya specific vehicle operator. The total risk may be used to determine oneor more costs associated with the insurance policy, such as a premiumand/or discount.

In some embodiments, information regarding the cost associated with theinsurance policy may be presented to the vehicle operator or insurancecustomer at block 416. The information may be presented by a display,such as the display 202 of the on-board computer 114 or the mobiledevice 110. The information may be presented either for informationalpurposes or to receive acceptance of the vehicle operator or insurancecustomer. The insurance cost information may include an indication ofone or more of a premium, rate, rating, discount, reward, special offer,points level, program, refund, and/or other costs associated with one ormore insurance policies. Additionally, or alternatively, summaryinformation may be presented regarding insurance costs, including a risklevel (e.g., high risk, low risk, a risk/cost level on a spectrum,etc.). in some embodiments, presentation of insurance cost informationmay be suppressed or delayed (e.g., cost information may be presented insummary form on a periodic billing statement).

In further embodiments, options or recommendations regarding the costassociated with the insurance policy may be presented to the vehicleoperator or insurance customer at block 418. The options orrecommendations may likewise be presented by a display, such as thedisplay 202 of the on-board computer 114 and/or the mobile device 110.The options or recommendations may include information regarding costsassociated with other settings or configurations of the autonomousoperation features (e.g., enabling additional features, selecting anoperating mode with lower risks under the determined environmentalconditions, etc.). In some embodiments, the recommendations or optionsmay be presented for informational purposes only, requiring the vehicleoperator or insurance customer to make any adjustments separatelythrough a settings module or other means of adjusting settings for theautonomous operation features). In other embodiments, the vehicleoperator or insurance customer may select one or more of the options,whereby adjustments to the configuration or settings of the autonomousoperation features may be caused to be implemented by the on-boardcomputer 114 or other controlling device, In some embodiments, theoptions or recommendations may include options or recommendations toupdate the software version of one or more autonomous operationfeatures, in which case information regarding a cost associated withupdating the features (if applicable) may be presented. Once theinformation and/or options or recommendations regarding insurance costshave been presented at blocks 416-418 (including, in some embodiments,while such presentation is occurring), the on-board computer 114 maymonitor operation of the vehicle 108.

At block 420, the on-board computer 114 may monitor operation of thevehicle 108, including autonomous operation feature control decisions,signals from the sensors 120, external data from the communicationcomponent 122, and/or control decisions of the vehicle operator.Monitoring vehicle operation may include monitoring data receiveddirectly from the features, sensors, and/or other components, as well assummary information regarding the condition, movement, and/orenvironment of the vehicle 108. The on-board computer 114 and/or mobiledevice 110 may cause the operating data to be stored or recorded, eitherlocally in the data storage 228 and/or via server 140 in the programmemory 160 and/or the database 146. Monitoring may continue untilvehicle operation is complete (e.g., the vehicle has reached itsdestination and shut down), including during any updates or adjustments.

At block 422, the on-board computer 114 may determine whether anychanges have been made to the settings or configuration of theautonomous operation features. If such changes or adjustments have beenmade, the on-board computer 114 may proceed to determine new risk levelsand insurance costs at blocks 412-414 and/or present the information tothe vehicle operator or insurance customer at blocks 416-418, asdiscussed above. In some embodiments, minor changes below a minimumchange threshold may be ignored when determining whether any changeshave been made. In further embodiments, the cumulate effect of aplurality of such minor changes below the minimum change threshold maybe considered as a change at block 422 when the cumulative effect of theminor changes reaches and/or exceeds the minimum change threshold. Whenno changes to the settings or configuration of the autonomous operationfeatures are determined to have been made at block 422, the on-boardcomputer 114 may further determine whether any changes in theenvironmental conditions and/or operating status of the autonomousoperation features or sensors have occurred. Although these steps areillustrated separately for clarity, it should be understood that theymay be further divided or combined in various embodiments.

At block 424, the on-board computer 114 may determine whether anychanges have occurred to the environmental conditions of the vehicle 108and/or the operating status of the autonomous operation features,sensors 120, or communication component 122. Such changes may occur whenweather or traffic conditions change, when sensors 120 malfunction orbecome blocked by debris, and/or when the vehicle 108 leaves an areawhere external data is available via the communication component 122.When such changes occur, the risk levels associated with control of thevehicle 108 by the vehicle operator and the autonomous operationfeatures may likewise change. Therefore, it may be advantageous toadjust the use of the autonomous operation features to account for suchchanges. Thus, the on-board computer 114 may proceed to determine newrisk levels and insurance costs at blocks 412-414 and/or present theinformation to the vehicle operator or insurance customer at blocks416-418, as discussed above, when such changes are determined to haveoccurred at block 424. Similar to the determination at block 422, minorchanges below a minimum change threshold may be ignored at block 424,unless the cumulative effect of the changes reaches or exceeds theminimum change threshold. When no changes are determined to haveoccurred at block 424, the method 400 may continue to monitor theoperation of the vehicle 108 until vehicle operation is determined tohave ended.

At block 426, the on-board computer 114 may determine whether vehicleoperations are complete. This may include determining whether a commandto shut down the vehicle 108 has been received, whether the vehicle 108has remained idle at a destination for a predetermined period of time,and/or whether the vehicle operator has exited the vehicle 108. Untiloperation is determined at block 426 to be complete (i.e., when thevehicle trip has concluded), the on-board computer 114 may continue tomonitor vehicle operation at block 420, as discussed above. Whenoperation is determined to be complete at block 426, the on-boardcomputer 114 may further cause a record of the operation of the vehicle108 to be made or stored. Such records may include operating data (infull or summary form) and may be used for assessing risks associatedwith one or more autonomous operation features or the vehicle operator.As noted above, in some embodiments, records of operating data may begenerated and stored continually during operation. in some embodiments,the partial or completed records may be transmitted to the server 140 tobe stored in the database 146. After completion and recordation of thevehicle operation, the method 400 may terminate.

Exemplary Methods for Determining Operating Status

FIG. 5 illustrates a flow diagram depicting an exemplary operatingstatus assessment method 500 that may be used to determine operationstatus of the autonomous operation features, sensors 120, and/orcommunication component 122, as indicated in blocks 404 and 424 above.The method 500 may evaluate the autonomous operation features of thevehicle 108 (including sensors 120) and determine whether they areoperating correctly, are malfunctioning, and/or are operating withimpaired or degraded quality. Such determinations may be particularlyimportant as the vehicle 108 ages or in environments that may block ordamage sensors 120. In such cases, the original effectiveness of theautonomous operation features may be reduced as sensors become lessaccurate or processing of the sensor data is slowed (such as by softwareversion updates that improve accuracy but require greater computationalresources). The exemplary method 500 may be implemented regularly toensure appropriate risk assessment, as well as periodically to certifythe operating status level of the vehicle for roadworthiness orinsurance rate adjustment. In some embodiments, periodic evaluation maybe performed using special purpose computing devices and/or by licensedor authorized third parties, Periodic evaluation may further includemore thorough testing and analysis of the vehicle 108, which may includetesting at a test environment. Although the exemplary embodiment isdescribed as primarily performed by the on-board computer 114, themethod 500 may be implemented by the mobile device 110, the on-boardcomputer 114, the server 140, or a combination thereof.

Upon receiving a request to determine the operating status of theautonomous operation features of the vehicle 108 at block 502, theconfiguration of the sensors 120 may be determined at block 504, Thefunctioning of autonomous operation feature software routines mayfurther be determined at block 506. A test signal may be transmitted tothe sensors 120 at block 508, and/or sensor data may be received atblock 510. The sensor data may include a response to the test signal, aswell as other signals from the sensors based upon the vehicleenvironment or operation of the vehicle 108, Based upon the receivedinformation, the operating status of the autonomous operation featuresand components may be determined at block 512. If any impairments aredetected at block 514, the method 500 may attempt to remediate theimpairments at block 516. If impairments are detected to remain at block518 after the remediation attempt, an alert may be generated andpresented to the vehicle operator or an insurance customer at block 520.When no impairments are detected or after presentation of the alert, areport indicating the operational status of the autonomous operationfeatures may be generated at block 522, In some embodiments, the reportmay be transmitted to an insurer at block 524, and/or a cost associatedwith an insurance policy associated with the vehicle 108 may bedetermined at block 526. The determined cost may be presented with thereport at block 528 to the vehicle operator or insurance customer. Oncethe report has been presented, the exemplary method may end.

At block 502, the on-board computer 114 may receive an indication of arequest to check the operating status of the autonomous operationfeatures of the vehicle 108. In some embodiments, the request may begenerated in response to a user interaction with the mobile device 110or a special-purpose computing device communicatively connected to thevehicle 108. For example, an application running on the mobile device110 may allow the user of the mobile device 110 to request an evaluationof the autonomous operation features. Similarly, a special-purposecomputing device may be connected to the vehicle 108 (wirelessly or viaa communication port) to evaluate the operating status of the autonomousoperation features. In other embodiments, the request may beautomatically generated by the on-board computer 114 in response to theoccurrence of an event, such as receipt of a command to start thevehicle, receipt of a command to shut off the vehicle, receipt of anindication of a collision involving the vehicle, and/or receipt of anindication of damage to the vehicle.

In yet further embodiments, the request may be generated by the server140 and transmitted to the on-board computer 114 to determine theoperating status of the autonomous operation features. Suchserver-generated requests may be used for insurance rating, and may begenerated periodically.

In some embodiments, the request may further include informationregarding the extent of the evaluation of the operating status of theautonomous operation features. For example, the request may indicatethat only software or sensors are to be evaluated, and/or the requestmay indicate one or more tolerances within which the system componentsmay be determined to be operating properly.

At block 504, the on-board computer 114 may determine the configurationof the sensors 120 disposed within or communicatively connected to thevehicle 108. This may include determining any of the number, type,location, technical specifications, and/or characteristics of thesensors 120. In further embodiments, the on-board computer 114 maydetermine normal functioning characteristics and/or output ranges forthe sensors 120, which may be used in determining whether the sensors120 are functioning normally. Determining normal functioningcharacteristics may include requesting such information from the server140 and/or accessing such information stored within the data storage228. In some embodiments, the configuration of one or more communicationcomponents 122 may also be determined at block 504.

At block 506, the on-board computer 114 may execute one or more softwarediagnostic routines to evaluate the operation of the software componentsof the autonomous operation features. In some embodiments, aspecial-purpose computing device and/or mobile device 110 may executethe routines or receive the output of the routines. The softwarediagnostic routines may cause test inputs to be presented to theautonomous operation features and receive responses based upon the testinputs. For example, the software diagnostic routines may simulatesensor inputs corresponding to a situation in which the autonomousoperation features should cause the vehicle to brake, then record thecontrol signals generated by the autonomous operation features. Ofcourse, the control signals output from the autonomous operation featuresoftware may be disconnected from the operating controls of the vehicle108 and/or suppressed during evaluation to prevent the vehicle 108 fromphysically responding to the test inputs.

At block 508, in some embodiments, the on-board computer 114 maygenerate and transmit one or more test signals to the sensors 120. Thetest signals may cause the sensors 120 to respond with statusinformation, such as verification of the communicative connection,signal quality, a predetermined set of response signals, and/or otherinformation regarding the sensors. In some embodiments, the test signalsmay cause the sensors 120 to enter a test mode or execute a calibrationroutine, in which case information regarding the operating status of thesensors 120 may be generated at the sensors 120 and transmitted to theon-board computer 114. in further embodiments, the on-board computer 114may further generate and transmit test signals to the communicationcomponent 122.

At block 510, the on-board computer 114 may receive sensor data from thesensors 120 or communication components 122. The received sensor datamay include responses to test signals. The received sensor data may, insome embodiments, also or alternatively include sensor data generated inthe ordinary course of operation of the sensors. For example, thereceived sensor data may include data indicating sensor readings ofobstacles within sensor range of the vehicle 108. Such ordinary coursesensor data may be combined and compared to determine the operatingstatus of each of a plurality of sensors connected to the vehicle 108.

At block 512, the on-board computer 114 may determine the operatingstatus of the autonomous operation features, including the sensors 120and/or the communication component 122, based upon the receivedinformation at blocks 506 and/or 510. This may include determining thesignal quality or accuracy of the sensor data and/or the accuracy orresponse time of the autonomous operation feature software. In someembodiments, determining the operating status of a sensor 120 mayinclude determining an expected sensor output signal based uponinformation received from other sensors 120 and comparing the actualoutput signal from the sensor to the expected output signal. To avoidminor deviations from expected sensor or software operation from beinginterpreted as a malfunction, a range of values indicating a normaloperating status may be allowed for the sensors and software. Thus, asensor signal within the normal range may be treated as indicating anormal operating status even if the value is slightly different from theexpected value. Additionally, sensors 120 from which no signal isreceived may be determined to be missing, malfunctioning, and/ordamaged. Some sensors 120 may further be determined to be blocked basedupon the received sensor data.

At block 514, the on-board computer 114 may determine whether any of theautonomous operation features, sensors 120, and/or communicationcomponents 122 have an impaired operating status. If all are operatingnormally, then the on-board computer 114 may proceed to generate areport at block 522. If any impairments are detected at block 514,however, the on-board computer 114 may attempt to remediate theimpairment at block 516. Remediation attempts may be determined basedupon the type of feature or component, as well as the type ofimpairment. For example, a remediation attempt for autonomous operationfeature software errors may include rebooting or reinstalling a portionof the software. As another example, a signal error in a sensor 120 maybe remediated by calibration of the sensor 120 based upon availablesensor data. Some vehicles 108 may include remediation components (notshown) for certain types of common impairments of sonic or all sensors120. For example, sensors 120 may become blocked by snow or ice in coldclimates, so heating elements may be disposed within the vehicle 108 tomelt accumulated snow or ice from an area around the sensors 120. Othertypes of blockages, such as by snow, ice, rain, dirt, mud, condensation,and/or other blockages, may be addressed with other remediationcomponents.

If remediation is determined at block 518 to successfully address allimpairments, a report may be generated at block 522. If one or moreimpairments remain, then an alert may be generated and presented to thevehicle operator or insurance customer at block 520. The alert mayinclude information regarding the type of autonomous operation featureor sensor impairment, the severity of the impairment, an impact on risksassociated with autonomous operation, whether some autonomous operationfeatures must be disabled, and/or recommendations regarding autonomousoperation features use and settings. In addition to the alert generatedand presented at block 520, the on-board computer 114 may generate areport at block 522.

At block 522, the on-board computer 114 may generate a report indicatingthe operating status of the autonomous operation features and componentsbased upon the information received at blocks 506 and 510. Ifremediation of one or more impairments has been attempted, the reportmay so indicate and/or may be adjusted based upon the results determinedat block 518. In some embodiments, the report may include informationregarding impaired features or sensors, while in other embodiments thereport may include information all features and sensors regarding. Infurther embodiments, the report may include recommendations regardingautonomous operation feature use or settings, as well as recommendationmaintenance or updates. In some embodiments, the report may include acertification of the operating status of the autonomous operationfeatures, sensors, and/or other components. In further embodiments, thereport may include information regarding maintenance performed on thevehicle 108, which may be recorded in the data storage 228. Where theevaluation is performed by an authorized or licensed third party,information regarding the third party may be included in the report.

At block 524, the report may be transmitted to a server 140 associatedwith an insurer for determination of costs or adjustments to one or moreinsurance policies. At block 526, the server 140 may determine one ormore costs associated with the one or more insurance policies based uponthe report. The one or more costs may include one or more of thefollowing: a premium, a discount, a surcharge, a rate level, a costbased upon a distance traveled, a cost based upon a vehicle trip, and/ora cost based upon a duration of vehicle operation. In some embodiments,the server 140 may first determine one or more adjustments to risklevels based upon the information in the report. For example, a risklevel associated with an autonomous operation feature may be increasedif one or more sensors used by the feature are impaired. The risk levelsmay be further used to determine costs based upon expected loss ratesfor the vehicle 108 and/or the vehicle operator.

At block 528, the report may be presented to the vehicle operator and/orinsurance customer by a display, such as display 202. The report may bepresented in full or may be summarized for ease of use some embodiments,the one or more costs associated with the insurance policy determined atblock 526 may also be presented. If the report includes a certificationof the status of the autonomous operation features and components, thecertification may also be presented to the vehicle operator and/orinsurance customer. In some embodiments, the certification may befurther transmitted to an account associated with the vehicle operatorand/or insurance customer and/or may be transmitted to a third party,such as a government agency. In some embodiments, the vehicle operatorand/or insurance customer may be presented with an option to save,record, print, and/or transmit the report.

FIG. 6 illustrates a flow diagram of an exemplary operating statusmonitoring method 600 that may be used to determine operation status ofthe autonomous operation features, sensors 120, and/or communicationcomponent 122, in addition to or alternatively to the exemplary method500 above. The method 600 may be implemented while the vehicle 108 is inoperation to monitor the operating status of the autonomous operationfeatures and components. The method 600 may monitor the vehicleoperating data at block 602 to determine operating status of theautonomous operation features and components at block 604 When a changein operating status is detected at block 606, one or more correspondingchanges in risk levels may be determined at block 608. If the changes inrisk levels are determined to cause the risk levels to exceed an alertthreshold but not a critical threshold at blocks 610 and 612,respectively, an alert is generated and presented to the vehicleoperator at block 614. If the risk levels are determined to exceed thecritical threshold at block 612, the method 600 may determine whethercontrol of the vehicle 108 can be safely transferred to the vehicleoperator at block 616. If the vehicle operator is prepared and able toassume control of the vehicle 108, then vehicle operation may betransferred to the vehicle operator at block 620. If control cannot besafely transferred, the vehicle 108 may cease operations and shut downat block 618. Once the vehicle 108 is no longer operating, the method600 may terminate. Although the exemplary embodiment is described asprimarily performed by the on-board computer 114, the method 600 may beimplemented by the mobile device 110, the on-board computer 114, theserver 140, or a combination thereof.

At block 602, the on-board computer 114 may monitor the operations ofthe vehicle 108 to obtain data regarding the autonomous operationfeatures and components. In some embodiments, this may include receivingand recording operating data from the autonomous operation features,sensors 120, and/or communication component 122. This vehicle operatingdata may be processed by the on-board computer 114 at block 604 todetermine the operation status of the autonomous operation features(including sensors 120 and/or communication component 122), as discussedabove.

At block 606, the on-board computer 114 may compare the operating statusinformation determined at block 604 with previously determined operatingstatus information. When no previous operating status information isavailable from the current or previous vehicle trip, the determinedoperating status information may be compared with baseline and/orexpected operating status information. In some embodiments, minorchanges to operating status may be disregarded at block 606, unless thecumulative effect of the changes exceeds a minimum threshold. The method600 may continue with monitoring the vehicle operation until a change inoperating status is determined at block 606. When a change isdetermined, the change in operating status may then be translated into achange in risk levels.

At block 608, the on-board computer 114 may determine one or morechanges in risk levels associated with operation of the vehicle 108 bythe autonomous operation features based upon the determined changes inoperating status. As discussed above, the changes in operating status ofthe autonomous operation features, sensors 120, and/or communicationcomponents 122 may cause risks associated with vehicle operation toincrease or decrease. For example, if a sensor 120 malfunctions, thechange in operating status of the sensor from operating normally tomalfunctioning may increase the risks associated with vehicle operationby limiting the sensor data available to one or more autonomousoperation features, thereby diminishing their effectiveness. If themalfunctioning sensor 120 were to later resume normal operation (e.g.,as a result of jostling or remediation), the additional sensor data maydecrease the risks associated with vehicle operation. In someembodiments, the on-board computer 114 and/or the server 140 may furtherdetermine an adjustment to a cost associated with an insurance policycovering the vehicle based upon the changes in operating statusadjustments to a premium, a discount, a surcharge, a rate level, a costbased upon a distance traveled, a cost based upon a vehicle trip, or acost based upon a duration of vehicle operation.). In addition tochanges in risk levels, the on-board computer 114 and/or server 140 mayfurther determine risk levels associated with operation of the vehiclebased upon the operating status and operating data.

At block 610, the on-board computer 114 may determine whether thechanges in one or more risk levels cause the total risk level or risklevels for one or more autonomous operation features to exceed the alertthreshold. If the alert threshold is not exceeded, the on-board computer114 may continue to monitor the operating data at block 602 for changesto operating status that may cause one or more risk levels to exceed thealert threshold. If the alert threshold is exceeded, the on-boardcomputer 114 may further determine whether the critical threshold foroperation is exceeded at block 612. If the critical threshold isexceeded, one or more autonomous operation features may no longer beable to safely control the vehicle 108 in the existing environmentalconditions. If the critical threshold is not exceeded, the autonomousoperation features may continue to control the vehicle 108, but withlower effectiveness.

If the critical threshold is determined not to be exceeded at block 612,the on-board computer 114 may generate and present to the vehicleoperator and/or insurance customer an alert indicating the impairment ofthe one or more autonomous operation features at block 614. The alertmay include information regarding the impairment, recommended actions toremediate or ameliorate the impairment (e.g., unblocking sensors,adjusting settings, etc.), relative risk levels, and/or otherinformation regarding the heightened risk associated with vehicleoperation. In some embodiments, the alert may further includeinformation regarding a change to a cost associated with an insurancepolicy based upon the changes in operating status, which may bedetermined by the on-board computer 114 or the server 140. In someembodiments, the alert may further include one or more options thevehicle operator may select to automatically adjust the settings of theautonomous operation features and/or attempt to remediate theimpairment.

If the critical threshold is exceeded, the on-board computer 114 maydetermine whether the vehicle operator is able and prepared to assumecontrol of one or more aspects of operation of the vehicle 108 from oneor more of the autonomous operation features at block 616. Determiningwhether the vehicle operator is able and prepared to safely accept atransfer of control may include determining one or more of risk levelsassociated with manual operation by the vehicle operator under theenvironmental conditions, the physical or mental state of the vehicleoperator, the attentiveness or alertness of the vehicle operator, and/orthe time available to transfer control of the vehicle 108, as describedin further detail below. If the vehicle operator is not prepared toaccept a transfer of vehicle operation from the one or more autonomousoperation features, the on-board computer 114 may cause the vehicle 108to safely stop at block 618. This may include causing the vehicle 108 tomaneuver out of traffic and/or into a position normally occupied bystationary vehicles. In some embodiments, the on-board computer 114 mayfurther shut down the engine or locomotive components of the vehicle 108and/or apply parking or locking devices to secure the vehicle 108 (e.g.,a parking brake). If the vehicle operator is prepared to accept atransfer of vehicle operation from the one or more autonomous operationfeatures, control of the one or more aspects of vehicle operation may betransferred to the vehicle operator at block 620. In some embodiments,the transfer may involve an alert or warning in advance of the transferof control, in order to provide the vehicle operator sufficient time toprepare to assume control of the vehicle 108. In some embodiments, thewarning period may depend upon the vehicle operating status, theenvironmental conditions, and/or the preparation level of the vehicleoperator.

Thus, according to certain aspects, the operating status and/orconfiguration of autonomous operation features of an autonomous orsemi-autonomous vehicle may be determined, such as via an on-boardcomputer system or mobile device, and/or then directly or indirectlywirelessly communicated via data transmission from the vehicle computersystem or mobile device to a remote server. An adjustment to one or morerisk levels associated with operation of the autonomous orsemi-autonomous vehicle may also be determined, and an auto insurancepolicy, premium, or discount may be adjusted based upon the adjustmentto the risk levels and presented to the customer for their review andapproval. As a result, insurance cost savings may be passed onto riskaverse customers that opt into to a rewards program.

With the foregoing, a customer may opt into a rewards or other type ofprogram, and willingly share their vehicle data with an insuranceprovider. In return, risk averse drivers and vehicle owners may receivediscounts or insurance cost savings related to auto and other types ofinsurance from the insurance provider.

Diagnostic Checks A. Abnormal Operating Condition

In one aspect, a computer-implemented method of enhancing vehicleoperation may be provided. The method may include (1) determining, viaone or more processors, that an autonomous or semi-autonomousfunctionality or technology of a vehicle is not operating correctly oroptimally, and/or otherwise is unsafe (or in an unsafe operatingcondition); (2) generating, via the one or more processors, a warning toa driver of the vehicle indicating that the autonomous orsemi-autonomous functionality or technology is not operating correctlyor optimally, and/or otherwise is unsafe; and/or (3) preventing, via theone or more processors, the driver of the vehicle from engaging orswitching on the autonomous or semi-autonomous functionality ortechnology that is not operating correctly or optimally, and/orotherwise is unsafe. The method may include additional, fewer, oralternate actions, including those discussed elsewhere herein.

For instance, the method may include (a) generating, via the one or moreprocessors, a wireless communication indicating that the autonomous orsemi-autonomous functionality or technology is not operating correctlyor optimally, and/or otherwise is unsafe; (b) transmitting, via the oneor more processors, the wireless communication to an insurance providerremote processor or server; and/or (c) adjusting or updating, at or viathe insurance provider remote processor or server, an insurance policy,premium, rate, rewards or points program, and/or discount for thevehicle based upon the autonomous or semi-autonomous functionality ortechnology not operating correctly or optimally, and/or otherwise beingunsafe.

The method may include (i) receiving, at or via the insurance providerremote processor or server, via wireless communication from a mobiledevice of an insured that the autonomous or semi-autonomousfunctionality or technology that was not operating correctly oroptimally was repaired and/or received maintenance, and/or is nowoperating correctly or optimally, and/or otherwise safely; and/or (ii)adjusting or updating, at or via the insurance provider remote processoror server, an insurance policy, premium, rate, rewards or pointsprogram, and/or discount for the vehicle based upon the autonomous orsemi-autonomous functionality or technology operating correctly oroptimally, and/or otherwise safely.

Determining, via the one or more processors, that the autonomous orsemi-autonomous functionality or technology of the vehicle is notoperating correctly or optimally may be based upon one or morepedestrians or traffic policeman being identified or recognized as beingwithin a vicinity of the vehicle. Additionally or alternatively, via theone or more processors, that the autonomous or semi-autonomousfunctionality or technology of the vehicle is not operating correctly oroptimally may be based upon a traffic light being identified orrecognized within a vicinity of the vehicle as not working or operatingcorrectly.

Determining, via the one or more processors, that the autonomous orsemi-autonomous functionality or technology of the vehicle is notoperating correctly or optimally may be based upon detecting a vehicleaccident ahead or road construction ahead. Additionally oralternatively, determining, via the one or more processors, that theautonomous or semi-autonomous functionality or technology of the vehicleis not operating correctly or optimally may be done through, or via, anelectric charging station and the vehicle may be an electric car orhybrid vehicle that has rechargeable batteries.

Determining, via the one or more processors, that the autonomous orsemi-autonomous functionality or technology of the vehicle is notoperating correctly or optimally may be based upon one or morediagnostic checks performed by the one or more processors. Additionallyor alternatively, determining, via the one or more processors, that theautonomous or semi-autonomous functionality or technology of the vehicleis not operating correctly or optimally may be based upon one or morediagnostic checks performed by an electric charging station (such as foran electric or hybrid vehicle).

Determining, via the one or more processors, that the autonomous orsemi-autonomous functionality or technology of the vehicle is notoperating correctly or optimally may be based upon one or morediagnostic checks performed by a gas station or smart fuel pump.Additionally or alternatively, determining, via the one or moreprocessors, that the autonomous or semi-autonomous functionality ortechnology of the vehicle is not operating correctly or optimally may bebased upon determining or detecting that one or more vehicle-mountedsensors (such as on an exterior of the vehicle) are covered by snow,ice, mud, touch-up or new paint, dust, and/or dirt. Further,determining, via the one or more processors, that the autonomous orsemi-autonomous functionality or technology of the vehicle is notoperating correctly or optimally may also be based upon determining ordetecting that software associated with the autonomous orsemi-autonomous functionality or technology has been corrupted, infectedwith a virus, needs updating to a newer software version, and/or hasbeen hacked into by a third party and/or has another security issue.

The method may further include (a) determining, at or via the insuranceprovider remote processor or server, that the insured or owner of thevehicle (and/or a computing device associated with the insured or owner)may not be configured to perform diagnostic checking (and/or does nothave an automated means for diagnostic checking) of the vehicle'sautonomous or semi-autonomous functionality or technology; (b) adjustingor generating, at or via the insurance provider remote processor orserver, an insurance policy, premium, rate rewards or points program,and/or discount for the vehicle based upon the lack of diagnosticchecking capabilities (and/or the lack of the automated means fordiagnostic checking) of the vehicle's autonomous or semi-autonomousfunctionality or technology; (c) communicating, at or via the insuranceprovider remote processor or server, a message or wireless communicationto the insured of updated or adjusted insurance policy, premium, raterewards or points program, and/or discount for the vehicle based uponthe lack of diagnostic checking capabilities (and/or the lack of theautomated means for diagnostic checking) of the vehicle's autonomous orsemi-autonomous functionality or technology; (d) generating, at or viathe insurance provider remote processor or server, a recommendation tothe insured or vehicle owner an automated means (and/or other means orfunctionality) for diagnostic checking of the vehicle's autonomous orsemi-autonomous functionality or technology, and/or an associatedinsurance-related cost savings associated with implementing therecommendation; and/or (e) transmitting, via the insurance providerremote processor or server, the recommendation, such as via wirelesscommunication, to a mobile device of the insured or vehicle owner tofacilitate automated diagnostic checking of the vehicle's autonomous orsemi-autonomous functionality or technology being implemented by theinsured or vehicle owner.

B. Verifying Diagnostic Checking Capabilities

In one aspect, a computer-implemented method of adjusting insurancepolicies may be provided. The method may include (1) determining, at orvia one or more processors (such as a local vehicle-mounted orhome-mounted processor, and/or an insurance provider remote processor orserver), that the insured or owner of the vehicle (and/or a computingdevice associated with the insured or owner) (i) may not be configuredfor diagnostic checking, (ii) may not have diagnostic checkingcapabilities or functionality, and/or (iii) may not have an automatedmeans (and/or other means or functionality, i.e., not configured) fordiagnostic checking of an autonomous or semi-autonomous functionality ortechnology of the vehicle; (2) adjusting or generating, at or via theone or more processors, an insurance policy, premium, rate rewards orpoints program, and/or discount for the vehicle based upon the lack ofthe diagnostic checking functionality or capabilities, and/or the lackof automated means (and/or other means or functionality) for diagnosticchecking of the vehicle's autonomous or semi-autonomous functionality ortechnology; (3) communicating, at or via the one or more processors, amessage or wireless communication to the insured of the updated oradjusted insurance policy, premium, rate rewards or points program,and/or discount for the vehicle based upon the lack of the diagnosticchecking functionality or capabilities, and/or the lack of the automatedmeans ((and/or other means or functionality) for diagnostic checking ofthe vehicle's autonomous or semi-autonomous functionality or technology;(4) generating, at or via the one or more processors, a recommendationto the insured or vehicle owner one or more diagnostic checking systemsor pieces of equipment, and/or an automated means (and/or other means orfunctionality) for diagnostic checking of the vehicle's autonomous orsemi-autonomous functionality or technology, and/or an associatedinsurance-related cost savings associated with implementing therecommendation; and/or (5) transmitting, under the direction or controlof the one or more processors, the recommendation, such as via wirelesscommunication, to a mobile device of the insured or vehicle owner tofacilitate automated diagnostic checking of the vehicle's autonomous orsemi-autonomous functionality or technology being implemented by theinsured or vehicle owner and/or providing an enticement to an insured tocheck performance or proper operation of autonomous or semi-autonomoustechnology and/or functionality. The method may include additional,fewer, or alternate actions, including those discussed elsewhere herein.

The method may include (a) receiving, at or via the insurance providerremote processor or server, via wireless communication from a mobiledevice of an insured that the insured or vehicle owner has acquired orimplemented the automated means (and/or other means or functionality)for diagnostic checking of the vehicle's autonomous or semi-autonomousfunctionality or technology; and/or (b) adjusting or updating, at or viathe insurance provider remote processor or server, an insurance policy,premium, rate, rewards or points program, and/or discount for thevehicle based upon the insured or vehicle owner having the diagnosticchecking functionality. Determining, at or via one or more processorsthat the insured or owner of the vehicle does not have diagnosticchecking functionality for the autonomous or semi-autonomousfunctionality or technology of the vehicle may be accomplished by, via,through communication with, and/or in conjunction with an electriccharging station, device, and/or power cord.

C. Electric Charging Station

In one aspect, a computer-implemented method of enhancing vehicleoperation may be provided. The method may include (1) determining, via,an electric charging station and/or an electric charging stationprocessor (such as for an electric or hybrid vehicle), that anautonomous or semi-autonomous functionality and/or technology of avehicle is not operating correctly or optimally, and/or otherwise isunsafe, based upon one or more diagnostic checks performed by theelectric charging station and/or the electric charging stationprocessor; (2) generating, via the one or more processors (such as aprocessor associated with the vehicle or electric charging station), awarning to a driver of the vehicle indicating that the autonomous orsemi-autonomous functionality and/or technology is not operatingcorrectly or optimally, and/or otherwise is unsafe (or is in an unsafeoperating condition); and/or (3) preventing, via the one or moreprocessors (such as one or more processors associated with the vehicleand/or electric charging station), the driver of the vehicle fromengaging or switching on the autonomous or semi-autonomous functionalityand/or technology that is not operating correctly or optimally, and/orotherwise is unsafe, to facilitate vehicle accident prevention or safervehicle operation. The method may include additional, fewer, oralternate actions, including those discussed elsewhere herein.

For instance, the method may further include (i) generating, via the oneor more processors, a wireless communication indicating that theautonomous or semi-autonomous functionality and/or technology is notoperating correctly or optimally, and/or otherwise is unsafe; (ii)transmitting, via the one or more processors, the wireless communicationto an insurance provider remote processor or server; and/or (iii)adjusting or updating, at or via the insurance provider remote processoror server, an insurance policy, premium, rate, rewards or pointsprogram, and/or discount for the vehicle based upon the autonomous orsemi-autonomous functionality and/or technology not operating correctlyor optimally, and/or otherwise being unsafe.

The method may further include (a) receiving, at or via the insuranceprovider remote processor or server, via wireless communication from amobile device of an insured that the autonomous or semi-autonomousfunctionality and/or technology that was not operating correctly oroptimally was repaired and/or received maintenance, and/or is nowoperating correctly or optimally, and/or otherwise safely; and/or (b)adjusting or updating, at or via the insurance provider remote processoror server, an insurance policy, premium, rate, rewards or pointsprogram, and/or discount for the vehicle based upon the autonomous orsemi-autonomous functionality and/or technology operating correctly oroptimally, and/or otherwise safely.

D. Remote Processor Or Server

In one aspect, a computer-implemented method of adjusting an insurancepolicy may be provided. The method may include (1) receiving, at or viathe insurance provider remote processor or server, via wired or wirelesscommunication an indication that an autonomous or semi-autonomousfunctionality and/or technology is operating correctly or optimally,and/or received periodic maintenance or a periodic safety certification;(2) generating, adjusting, or updating, at or via the insurance providerremote processor or server, an insurance policy, premium, rate, rewardsor points program, and/or discount for the vehicle based upon theautonomous or semi-autonomous functionality and/or technology operatingcorrectly or optimally, and/or receiving periodic maintenance orperiodic safety certification; and/or (3) generating and transmitting,at or from the insurance provider remote processor server, to a mobiledevice of an insured via wireless communication a notification of theinsurance policy, premium, rate, rewards or points program, and/ordiscount that has been generated, adjusted, or updated based upon theautonomous or semi-autonomous functionality and/or technology operatingcorrectly or optimally, and/or receiving periodic maintenance orperiodic safety certification. The method may include additional, fewer,or alternate actions, including those discussed elsewhere herein.

The method may include (i) receiving, at or via the insurance providerremote processor or server, via wired or wireless communication anindication that the autonomous or semi-autonomous functionality and/ortechnology is not operating correctly or optimally, and/or has notreceived periodic maintenance or a periodic safety certification; (ii)generating, adjusting, or updating, at or via the insurance providerremote processor or server, an insurance policy, premium, rate, rewardsor points program, and/or discount for the vehicle based upon theautonomous or semi-autonomous functionality and/or technology notoperating correctly or optimally, and/or not receiving periodicmaintenance or periodic safety certification; and/or (iii) generatingand transmitting, at or from the insurance provider remote processorserver, to the mobile device of the insured via wireless communication anotification of the insurance policy, premium, rate, rewards or pointsprogram, and/or discount that has been generated, adjusted., or updatedbased upon the autonomous or semi-autonomous functionality and/ortechnology not operating correctly or optimally, and/or not receivingperiodic maintenance or periodic safety certification.

Exemplary Methods For Control Hand-Off

FIGS. 7A-B illustrate flow diagrams depicting exemplary vehicleoperation hand-off methods 700 that may he used to transfer operation ofthe vehicle 108 from one or more autonomous operation features to thevehicle operator. FIG. 7A illustrates hand-off of control whendetermined necessary based upon heightened risk levels associated withoperation by the one or more autonomous operation features under theenvironmental conditions. FIG. 7B illustrates hand-off of control whenrequested by the vehicle operator while one or more autonomous operationfeatures are performing vehicle control tasks. The methods 700illustrated in FIGS. 7A and 7B may be combined or separately implementedin various embodiments. Although the exemplary embodiment is describedas primarily performed by the on-board computer 114, the exemplarymethod 700 may be implemented by the mobile device 110, the on-boardcomputer 114, the server 140, and/or a combination thereof.

Exemplary vehicle operation hand-off method 700 may be implemented atany time when one or more autonomous operation features are controllingpart or all of the operation of the vehicle 108. The method 700 maybegin by identifying the vehicle operator at block 702 and receiving avehicle operator profile for the vehicle operator at block 704. At block706, the operating data (including, in some embodiments, sensor data andexternal data) may be received and used to monitor operation of thevehicle 108. In some embodiments, a request to disable one or moreautonomous operation features may be received from the vehicle operatorat block 732. Autonomous risk levels associated with operation of thevehicle 108 by the autonomous operation features and operator risklevels associated with operation of the vehicle 108 by the vehicleoperator may be determined at block 708 and 710, respectively. Thedetermined risk levels may be used at block 712 to determine whether todisable one or more autonomous operation features. In some embodiments,the determination of whether to disable one or more autonomous operationfeatures may further be based upon the preparedness level of the vehicleoperator determined at block 716.

When it is determined to disable one or more autonomous operationfeatures at block 714, the method 700 may transfer control to thevehicle operator. In some embodiments, this may include determiningwhether the vehicle operator is able to safely assume control bydetermining whether the vehicle operator's preparedness level is above atransfer threshold level at block 718. If so, an alert may be presentedto the vehicle operator at block 720 to notify the vehicle operator ofthe transfer of control from the one or more autonomous operationfeatures before transferring operation at block 722. If the vehicleoperator's preparedness level is determined to be below the transferthreshold but above a minimum threshold at block 724, an alert may bepresented at block 730 to attempt to prepare the vehicle operator toassume control if the risk levels associated with continued operation bythe autonomous operation features do not exceed a critical riskthreshold at block 726. Once the alert is presented to the vehicleoperator at block 730, the vehicle operator's preparedness level may bedetermined again at block 716 and evaluated at block 718. If the risklevels exceed the critical threshold at block 726 or the vehicleoperator's preparedness level is below the minimum threshold at block724, the vehicle 108 may discontinue operation at block 728 and themethod 700 may end.

When it is determined not to disable the one or more autonomousoperation features at block 714, the method 700 may continue to monitorthe operating data at block 706, If the vehicle operator requested thatone or more autonomous operation features be disabled, the method 700may present an alert at block 734 to notify the vehicle operator thatdisabling the autonomous operation features is not recommended. In someembodiments, options to override the determination not to disable theautonomous operation features may be presented to the vehicle operatorat block 736, which the vehicle operator may select at block 738. If thevehicle operator is determined at block 740 to have not selected anoption to override the determination, the method 700 may continue tomonitor operation data at block 706. If the vehicle operator isdetermined at block 740 to have selected an option to override thedetermination, control of operation may be transferred from the one ormore autonomous operation features to the vehicle operator. In someembodiments, one or more risk levels associated with disabling theautonomous operation features may be determined at block 742. If therisk levels are determined to be below a critical threshold at block744, control may be transferred to the vehicle operator. If the risklevels meet or exceed the critical threshold at block 744, the vehicle108 may instead discontinue operation at block 728 and the method 700may end.

Exemplary Methods for Vehicle Operator Identification

FIG. 8 illustrates a flow diagram depicting an exemplary vehicleoperator identification method 800 that may be used to adjust aninsurance policy associated with the vehicle operator or vehicle 108.The exemplary method 800 may begin with receipt of a request to identifythe vehicle operator of the vehicle at block 802. At blocks 804-810, thevehicle operator may be identified by sensor data or receivedindications of identity, such as from a mobile device 110. Once theidentity of the vehicle operator has been determined (or cannot bedetermined), the method 800 may further determine whether the vehicleoperator is authorized to operate the vehicle 108 at block 812. If thevehicle operator is not authorized, an alert may be generated andvehicle operations may be limited at blocks 814-816. If the vehicleoperator is authorized, a vehicle operator profile associated with thevehicle operator may be obtained at block 818, and/or an insurancepolicy associated with the vehicle 108 or the vehicle operator may beidentified at block 820. During vehicle operation, operating data of thevehicle 108 may be received and used to adjust the vehicle operatorprofile and the insurance policy at blocks 822-826. When vehicleoperation has been determined to be complete at block 828, the method800 may terminate. Although the exemplary embodiment is described asprimarily performed by the on-board computer 114, the method 800 may beimplemented by the mobile device 110, the on-board computer 114, theserver 140, and/or a combination thereof.

Exemplary Methods for Monitoring Use by Vehicle Operators

FIG. 9 illustrates a flow diagram depicting an exemplary vehicleoperator use monitoring and evaluation method 900 that may be used todetermine skill or risk levels associated with a vehicle operator oradjust an insurance policy. The exemplary method 900 may begin withdetermining the identity of the vehicle operator at block 902. If avehicle operator profile can be found for the vehicle operator at block904, the vehicle operator profile may be accessed at block 912. If novehicle operator profile can be found for the vehicle operator at block904, a vehicle operator profile may be created based upon vehicleoperations and stored for future use at blocks 906-910. The newlycreated vehicle operator profile may be generated at block 908 withvehicle operating data from only a short time period or may include onlyinformation regarding configuration and/or settings of the autonomousoperation features, in which case operation of the vehicle may continueafter the vehicle operator profile is generated. If operation isdetermined to be ongoing at block 914, vehicle operation may bemonitored and the vehicle operator profile may be updated at blocks916-924. In some embodiments, the vehicle operator may be able to selectan option of a mode for vehicle operation. If such a mode selection isdetected at block 916, the settings of the autonomous operation featuresmay be adjusted at block 918. Vehicle operation may be monitored atblock 920 based upon received operating data, which may be used todetermine adjustments to the vehicle operator profile at block 922. Theadjustments may then be used to update the vehicle operator profile atblock 924. When operation is complete, the method 900 may determine riskor skill levels associated with the vehicle operator at blocks 926-928.These determined levels may be used at blocks 930-934 to generate areport or adjust an insurance policy. Although the exemplary embodimentis described as primarily performed by the on-board computer 114, themethod 900 may be implemented by the mobile device 110, the on-boardcomputer 114, the server 140, and/or a combination thereof.

The vehicle operator profile may include information regarding thevehicle operator, including an operating style of the vehicle operation.The operating style may include information regarding frequency withwhich the vehicle operator operates the vehicle manually, uses one ormore autonomous operation features, selects one or more settings for theautonomous operation features, and/or takes control from the autonomousoperation features under various conditions. The operating style mayfurther include information regarding observed control decisions made bythe vehicle operator, such as rate of acceleration, frequency of lanechanges, use of vehicle signaling devices, distances maintained fromother vehicles or pedestrians, and/or other aspects of vehicleoperation. For example, vehicle operator decisions regarding how long tostop at a stop sign or when to begin accelerating from such a stop inthe presence of other vehicles or pedestrians may be included in theoperating style. The vehicle operator profile may further includeinformation regarding vehicle operator skill levels, as described below.In some embodiments, the vehicle operator profile may include a riskprofile or information regarding one or more risk levels associated withoperation of the vehicle by the vehicle operator. Such risk levels maybe associated with particular configurations or settings of autonomousoperation features and/or particular conditions of the vehicleenvironment (e.g., time of day, traffic levels, weather, etc.

In further embodiments, the vehicle operator profile may includeinformation regarding attentiveness of the vehicle operator while thevehicle is being autonomously operated. For example, some vehicleoperators may typically pay attention to road conditions while a vehicleis operating in a fully autonomous anode, while other vehicle operatorsmay typically engage in other activities. In some embodiments, thevehicle operator profile may include information regarding decisionsmade by the vehicle operator regarding actions that would result inadjustments to costs associated with an insurance policy (e.g.,accepting or rejecting recommendations to optimize autonomous operationfeature use to lower insurance costs).

The vehicle operator profile or vehicle operator behavior data mayindicate how well the specific vehicle operator drives in rain, snow,sleet, ice, heavy traffic, road construction, stop-and-go traffic,bumper-to-bumper traffic, country or rural traffic, and/or city ordowntown street traffic. The current environment (or condition) mayinclude or be rain, ice, snow, fog, heavy traffic, bumper-to-bumpertraffic, road construction, city traffic, country or rural traffic,and/or may be associated with a type of road, such as a two-lane orfour-lane highway, and/or downtown city street or other street havingseveral traffic lights.

The operating mode may include one or more settings or configurations ofautonomous operation features. For example, operating modes may includeadjustments to settings that cause the autonomous operation features tocontrol the vehicle 108 in a more or less aggressive manner with respectto speed, distance from other vehicles, distance from pedestrians, etc.As an example, the settings may cause the vehicle 108 to remain at leasta minimum distance from other vehicles may depend upon vehicle speed orroad conditions), and/or modes may set different minimum distances.Examples of modes may include a city driving mode, a highway drivingmode, a rush operation mode, a smooth operation mode, a cautious mode,and/or a user-defined mode.

In some embodiments, an operating mode may be based upon the vehicleoperator profile. For example, the vehicle profile may includeinformation indicating an operating style of the vehicle operator basedupon observations of control commands by the vehicle operator, whichprofile information may be used to generate an operation mode thatmimics the style of the vehicle operator. Thus, if the vehicle operatortypically stops at stop signs for a particular length of time, theoperating style may mimic this length of time to provide an experiencethat seems normal or customary to the vehicle operator.

Exemplary Methods For Comparing Costs

FIG. 10 illustrates a flow diagram depicting an exemplary costcomparison method 1000 that may be used to compare costs associated withvehicles, some of which may include autonomous operation features. Theexemplary method 1000 may begin by receiving a command to generate acomparison report between two or more alternative transportation optionsfor an insurance customer or other user. The method 1000 may furtherreceive information regarding one or more vehicle operators may bereceived at block 1004 and/or information regarding a first vehicle anda second vehicle at block 1006. The first and second vehicles may differin autonomous operation features or other characteristics. Cost levelsassociated with obtaining, operating, and insuring the first vehicle andthe second vehicle may be determined at block 1008, and/or arecommendation based upon the costs may be determined at block 1010. Areport including the costs levels, recommendation, and/or relatedinformation may be generated at block 1012 and presented to theinsurance customer or other user at block 1014. Additionally, one ormore options may be presented along with the report at block 1016, suchas options to perform another comparison or present additionalinformation, if an option is selected at block 1018, the correspondingaction may be performed at block 1020. Although the exemplary embodimentis described as primarily performed by the server 140, the method 1000may be implemented by the mobile device 110, the on-board computer 114,the server 140, and/or a combination thereof.

Exemplary Methods for Updating Autonomous Operation Features

FIG. 11 illustrates a flow diagram depicting an exemplary autonomousoperation feature update method 1100 that may be used to identify,recommend, and/or install updates to autonomous operation features inappropriate autonomous or semi-autonomous vehicles. In some embodiments,the updates may include software version updates. The exemplary method1100 may begin with the receipt of an indication of an available updateto an autonomous operation feature at block 1102, which may include anupdate to a version of autonomous operation feature software. Aplurality of vehicles having the autonomous operation feature may beidentified at block 1104 based upon recorded features or communicationwith the plurality of vehicles. A change in one or more risk levelsassociated with the update may be determined for some or all of theidentified vehicles at block 1106, and/or a change in a cost associatedwith one or more of the plurality of vehicles may be determined at block1108. If the determined changes in risk levels or insurance costs meetcertain criteria, for installing the update at block 1110, anotification regarding the update may be presented to an insurancecustomer at block 1112. The notification may further include informationregarding costs associated with the update. If an indication ofacceptance of the update is received at block 1114, the update may beinstalled at block 1116. Although the exemplary embodiment is describedas primarily performed by the server 140, the method 1100 may beimplemented h the mobile device 110, the on-board computer 114, theserver 140, and/or a combination thereof.

Exemplary Methods for Repair of an Autonomous Vehicle

FIG. 12 illustrates a flow diagram depicting an exemplary autonomousvehicle repair method 1200 that may be used to determine repairs neededas a result of damage to an autonomous or semi-autonomous vehicle. Theexemplary method 1200 may begin by receiving an indication of damage tothe vehicle 108 at block 1202 and/or receiving operating data associatedwith the vehicle 108 at block 1204. Based upon the operating data, thetype and extent of damage to the vehicle 108 may be determined at block1206, and/or repairs needed to fix the damage may be determined at block1208. Additionally, one or more expected costs (or ranges of costs) forthe repairs may be estimated at block 1210. An insurance policyassociated with the vehicle 108 may be identified, and/or a maximumpayment for the repairs may be determined at block 1212 based upon theestimated costs and the insurance policy. Information regarding theestimated cost or costs and the maximum payment under the insurancepolicy may be presented to an insurance customer at block 1214.Additionally, options associated with the repairs may be presented tothe insurance customer at block 1216, and/or a selection of one or moreoptions may be received at block 1218. An insurer or other party maycause a payment to he made at block 1220 to the insurance customer,beneficiary, or other relevant party based upon the estimated costs ofrepairing the damage and the selected option. Although the exemplaryembodiment is described as primarily performed by the server 140, themethod 1200 may be implemented by the mobile device 110, the on-boardcomputer 114, the server 140, and/or a combination thereof.

Exemplary Methods for Infrastructure Communications

FIG. 13 illustrates a flow diagram depicting an exemplary infrastructurecommunication method 1300 that may be used to detect and communicateinformation regarding infrastructure components to vehicles. Theexemplary method 1300 may begin with the infrastructure communicationdevice 124 receiving information regarding the infrastructure component126 from one or more sensors at block 1302. The information may be usedat block 1304 to determine a message regarding the infrastructurecomponent 126. In some embodiments, the message may be augmented atblock 1306 by information associated with a sponsor or other partyaffiliated with the infrastructure communication device 124. The messagemay then be encoded at block 1308 and transmitted at block 1310, whichmay cause the message to be presented to the vehicle operator of thevehicle 108 at block 1312, Although the exemplary embodiment describesone infrastructure communication device 124 communicating with onevehicle 108, it should be understood than any number of infrastructurecommunication devices 124 may communicate with any number of vehicles108.

Updating Insurance Policies

In one aspect, a computer-implemented method of updating an insurancepolicy may be provided. The method may include (a) gathering orreceiving, at or via one or more processors (such as either a localprocessor associated with a smart vehicle and/or a remote processor orserver associated with an insurance provider), data indicative of (1)vehicle usage, and/or (2) vehicle drivers for an insured vehicle; (b)analyzing the data, via the one or more processors, to determine (i) anamount and/or (ii) type of vehicle usage for each vehicle driver; (c)based upon the amount of vehicle usage for each vehicle driver and/orthe type of vehicle usage for each vehicle driver, via the one or moreprocessors, updating or adjusting an insurance policy (such as apremium, rate, rewards or points program, discount, etc.) for theinsured vehicle; (d) transmitting, under the direction or control of theone or more processors, the updated or adjusted insurance policy (orotherwise causing the updated or adjusted insurance policy to bepresented or displayed to the insured) to a mobile device of the insuredfor their review, modification, and/or approval; and/or (e) receiving,at or via the one or more processors, from the mobile device of theinsured (such as via wireless communication) an approval of the updatedor adjusted insurance policy of the insured to facilitate more accurateinsurance pricing and/or insurance cost savings. The method may includeadditional, fewer, or alternate actions, including those discussedelsewhere herein.

For instance, the amount of vehicle usage may include an amount of timeand/or miles that each individual vehicle driver drives the vehicle. Thetype of vehicle usage may include characterizing various periods ofdriving and/or trips as city driving; country driving; freeway orhighway driving city street driving; heavy traffic or congested trafficdriving; driving in good weather; driving in hazardous weather; rushhour driving; and/or time-of-day driving.

The vehicle drivers may be identified from mobile device signature; seatpressure sensors and weight; image recognition techniques performed uponimages of the driver; and/or biometric devices (such as heart beat orrate characteristics; voice print; and/or thumb or finger prints).

Biometric Device Data

In one aspect, a computer-implemented method of updating an insurancepolicy using biometric device data may be provided. The method mayinclude (a) gathering or receiving, at or via one or more processors(such as either a local processor associated with a smart vehicle and/ora remote processor or server associated with an insurance provider),data from a biometric device indicative of whom is driving an insuredvehicle; (b) gathering or receiving, at or via the one or moreprocessors, data indicative of vehicle usage for a single trip and/ordriving or driver behavior during the single trip; (c) updating oradjusting, at or via the one or more processors, an insurance policy(such as a premium, rate, rewards or points program, discount, etc.) forthe insured vehicle based upon (1) whom is driving the insured vehicle(and/or his or her driving profile or score), and/or (2) the dataindicative of vehicle usage for the single trip and/or the driving ordriver behavior exhibited during the single trip to facilitate moreaccurate risk assessment and/or cost savings to the insured. The methodmay include additional, fewer, or alternate actions, including thosediscussed elsewhere herein. For instance, the biometric device mayverify an identity of the driver based upon heartbeat, facialrecognition techniques, and/or mood.

In another aspect, a computer-implemented method of updating aninsurance policy may be provided. The method may include (1) gatheringor receiving, at or via one or more processors (such as either a localprocessor associated with a smart vehicle and/or a remote processor orserver associated with an insurance provider), data from a biometricdevice identifying a driver of an insured vehicle; (2) gathering orreceiving, at or via the one or more processors, data indicative ofdriving or driver behavior for the driver identified from the biometricdevice data; (3) generating, at or via the one or more processors, ausage-based insurance policy for the insured vehicle based upon (i) theidentity of the driver determined from the biometric device data, and/or(ii) the data indicative of driving or driver behavior exhibited by thedriver to facilitate more accurate risk assessment and/or provide costsavings to the insured. The method may include additional, fewer, oralternate actions, including those discussed elsewhere herein.

Software Versions

In one aspect, a computer-implemented method of updating an insurancepolicy may be provided. The method may include (1) gathering orreceiving, at or via one or more processors (such as either a localprocessor associated with a smart vehicle and/or a remote processor orserver associated with an insurance provider), data indicative of asoftware version installed on or in an insured vehicle that isassociated with an autonomous or semi-autonomous functionality; (2)determining, at or via the one or more processors, that the softwareversion is out of date or a (safer or less risky) new software versionexists and/or is available for download; (3) generating, at or via theone or more processors, a recommendation to an insured to update orupgrade to the new software version, and transmitting thatrecommendation under the direction or control of the one or moreprocessors to a mobile device or insured vehicle controller (such as viawireless communication or data transmission); (4) determining, at or viathe one or more processors, (or receiving an indication) that theinsured has updated or upgraded to the new software version associatedwith the autonomous or semi-autonomous functionality; and/or (5)updating or adjusting, at or via the one or more processors, aninsurance policy (such as a premium, rate, rewards or points program,discount, etc.) for the insured vehicle based upon the insured updatingor upgrading to the new software version associated with an autonomousor semi-autonomous functionality to facilitate providing cost savings tothe insured and/or enticing drivers to update vehicle software to mostrecent versions and/or versions that perform better. The method mayinclude additional, fewer, or alternate actions, including thosediscussed elsewhere herein.

Exemplary Autonomous Vehicle Insurance Risk and Price DeterminationMethods

Risk profiles or risk levels associated with one or more autonomousoperation features determined above may be further used to determinerisk categories or premiums for vehicle insurance policies coveringautonomous vehicles. In some embodiments or under some conditions, thevehicle 108 may be a fully autonomous vehicle operating without avehicle operator's input or presence. In other embodiments or underother conditions, the vehicle operator may control the vehicle 108 withor without the assistance of the vehicle's autonomous operationfeatures. For example, the vehicle may be fully autonomous only above aminimum speed threshold or may require the vehicle operator to controlthe vehicle during periods of heavy precipitation. Alternatively, theautonomous vehicle may perform all relevant control functions using theautonomous operation features under all ordinary operating conditions,in still further embodiments, the vehicle 108 may operate in either afully or a partially autonomous state, while receiving or transmittingautonomous communications.

Where the vehicle 108 operates only under fully autonomous control bythe autonomous operation features under ordinary operating conditions orwhere control by a vehicle operator may be disregarded for insurancerisk and price determination, the risk level or premium associated withan insurance policy covering the autonomous vehicle may he determinedbased upon the risks associated with the autonomous operation features,without reference to risks associated with the vehicle operator. Wherethe vehicle 108 may be operated manually under some conditions, the risklevel or premium associated with an insurance policy covering theautonomous vehicle may be based upon risks associated with both theautonomous operation features and the vehicle operator performing manualvehicle operation. Where the vehicle 108 may be operated with theassistance of autonomous communications features, the risk level orpremium associated with an insurance policy covering the autonomousvehicle may be determined based in part upon a determination of theexpected use of autonomous communication features by external sources inthe relevant environment of the vehicle 108 during operation of thevehicle 108.

Data Acquisition

In one aspect, the present embodiments may relate to data acquisition.Data may be gathered via devices employing wireless communicationtechnology, such as Bluetooth or other IEEE communication standards. Inone embodiment, a Bluetooth enabled smartphone or mobile device, and/oran in-dash smart and/or communications device may collect data. The dataassociated with the vehicle, and/or vehicle or driver performance, thatis gathered or collected at, or on, the vehicle may be wirelesslytransmitted to a remote processor or server, such as a remote processoror server associated with an insurance provider. The mobile device 110may receive the data from the on-board computer 114 or the sensors 120,and may transmit the received data to the server 140 via the network130, and the data may be stored in the database 146. In someembodiments, the transmitted data may include real-time sensor data, asummary of the sensor data, processed sensor data, operating data,environmental data, communication data, or a log such data.

Data may be generated by autonomous or semi-autonomous vehicles and/orvehicle mounted sensors (or smart sensors), and then collected byvehicle mounted equipment or processors, including Bluetooth devices,and/or an insurance provider remote processor or server. The datagathered may be used to analyze vehicle decision making. A processor maybe configured to generate data on what an autonomous or semi-autonomousvehicle would have done in a given situation had the driver not takenover manual control/driving of the vehicle or alternative controlactions not taken by the autonomous or semi-autonomous operationfeatures. This type of control decision data (related to vehicledecision making) may be useful with respect to analyzing hypotheticalsituations.

In one embodiment, an application, or other computer or processorinstructions, may interact with a vehicle to receive and/or retrievedata from autonomous or semi-autonomous processors and sensors. The dataretrieved may be related to radar, cameras, sensor output, computerinstructions or application output. Other data related to a smartvehicle controller, car navigation unit information (including routehistory information and typical routes taken), GPS unit information,odometer and/or speedometer information, and smart equipment data mayalso be gathered or collected. The application and/or other computerinstructions may be associated with an insurance provider remoteprocessor or server.

The control decision data may further include information regardingcontrol decisions generated by one or more autonomous operation featureswithin the vehicle. The operating data and control decision datagathered, collected, and/or acquired may facilitate remote evaluationand/or analysis of what the autonomous or semi-autonomous vehicle was“trying to do” (brake, slow, tum, accelerate, etc.) during operation, aswell as what the vehicle actually did do. The data may reveal decisions,and the appropriateness thereof, made by the artificial intelligence orcomputer instructions associated with one or more autonomous orsemi-autonomous vehicle technologies, functionalities, systems, and/orpieces of equipment. The data may include information related to whatthe vehicle would have done in a situation if the driver had not takenover (beginning manual vehicle control). Such data may include both thecontrol actions taken by the vehicle and control actions the autonomousor semi-autonomous operation features would have caused the vehicle totake. Thus, in some embodiments, the control decisions data may includeinformation regarding control decisions not implemented by theautonomous operation features to control the vehicle. This may occurwhen an autonomous operation feature generates a control decision orassociated control signal, but the control decision or signal isprevented from controlling the vehicle because the autonomous feature orfunction is disabled, the control decision is overridden by the vehicleoperator, the control signal would conflict with another control signalgenerated by another autonomous operation feature, a more preferredcontrol decision is generated, and/or an error occurs in the on-boardcomputer 114 or the control system of the vehicle.

For example, a vehicle operator may disable or constrain the operationof some or all autonomous operation features, such as where the vehicleis operated manually or semi-autonomously. The disabled or constrainedautonomous operation features may, however, continue to receive sensordata and generate control decision data. that is not implemented.Similarly, one or more autonomous operation features may generate morethan one control decision in a relevant period of time as alternativecontrol decisions. Some of these alternative control decisions may notbe selected by the autonomous operation feature or an autonomousoperation control system to control the vehicle. For example, suchalternative control decisions may be generated based upon different setsof sensor or communication data from different sensors 120 or include orexcluding autonomous communication data. As another example, thealternative control decisions may be generated faster than they can beimplemented by the control system of the vehicle, thus preventing allcontrol decisions from being implemented.

In addition to control decision data, other information regarding thevehicle, the vehicle environment, or vehicle operation may be collected,generated, transmitted, received, requested, stored, and/or recorded inconnection with the control decision data. Additional operating dataincluding sensor data from the sensors 120, autonomous communicationdata from the communication component 122 or the communication unit 220,location data., environmental data, time data, settings data,configuration data, and/or other relevant data may be associated withthe control decision data. In some embodiments, a database or log maystore the control decision data and associated information. In furtherembodiments, the entries in such log or database may include a timestampindicating the date, time, location, vehicle environment, vehiclecondition, autonomous operation feature settings, and/or autonomousoperation feature configuration information associated with each entry.Such data may facilitate evaluating the autonomous or semi-autonomoustechnology, functionality, system, and/or equipment in hypotheticalsituations and/or may be used to calculate risk, and in turn adjustinsurance policies, premiums, discounts, etc.

Autonomous Vehicle Insurance Policies

The disclosure herein relates to insurance policies for vehicles withautonomous operation features. Accordingly, as used herein, the term“vehicle” may refer to any of a number of motorized transportationdevices. A vehicle may be a car, truck, bus, train, boat, plane,motorcycle, snowmobile, other personal transport devices, etc. Also asused herein, an “autonomous operation feature” of a vehicle means ahardware or software component or system operating within the vehicle tocontrol an aspect of vehicle operation without direct input from avehicle operator once the autonomous operation feature is enabled orengaged. The term “autonomous vehicle” means a vehicle including atleast one autonomous operation feature. A “fully autonomous vehicle”means a vehicle with one or more autonomous operation features capableof operating the vehicle in the absence of or without operating inputfrom a vehicle operator.

Additionally, the term “insurance policy” or “vehicle insurance policy,”as used herein, generally refers to a contract between an insurer and aninsured. In exchange for payments from the insured, the insurer pays fordamages to the insured which are caused by covered perils, acts, orevents as specified by the language of the insurance policy. Thepayments from the insured are generally referred to as “premiums,” andtypically are paid by or on behalf of the insured upon purchase of theinsurance policy or over time at periodic intervals. Although insurancepolicy premiums are typically associated with an insurance policycovering a specified period of time, they may likewise be associatedwith other measures of a duration of an insurance policy, such as aspecified distance traveled or a specified number of trips. The amountof the damages payment is generally referred to as a “coverage amount”or a “face amount” of the insurance policy. An insurance policy mayremain (or have a status or state of) “in-force” while premium paymentsare made during the term or length of coverage of the policy asindicated in the policy. An insurance policy may “lapse” (or have astatus or state of “lapsed”), for example, when the parameters of theinsurance policy have expired, when premium payments are not being paid,when a cash value of a policy falls below an amount specified in thepolicy, or if the insured or the insurer cancels the policy. 101611 Theterms “insurer,” “insuring party,” and “insurance provider” are usedinterchangeably herein to generally refer to a party or entity (e.g., abusiness or other organizational entity) that provides insuranceproducts, e.g., by offering and issuing insurance policies. Typically,but not necessarily, an insurance provider may be an insurance company.The terms “insured,” “insured party,” “policyholder,” and “customer” areused interchangeably herein to refer to a person, party, or entity(e.g., a business or other organizational entity) that is covered by theinsurance policy, e.g., whose insured article or entity is covered bythe policy. Typically, a person or customer (or an agent of the personor customer) of an insurance provider fills out an application for aninsurance policy. In some cases, the data for an application may beautomatically determined or already associated with a potentialcustomer. The application may undergo underwriting to assess theeligibility of the party and/or desired insured article or entity to becovered by the insurance policy, and, in some cases, to determine anyspecific terms or conditions that are to be associated with theinsurance policy, e.g., amount of the premium, riders or exclusions,waivers, and the like. Upon approval by underwriting, acceptance of theapplicant to the terms or conditions, and payment of the initialpremium, the insurance policy may be in-force, (i.e., the policyholderis enrolled).

Although the exemplary embodiments discussed herein relate to automobileinsurance policies, it should be appreciated that an insurance providermay offer or provide one or more different types of insurance policies.Other types of insurance policies may include, for example, commercialautomobile insurance, inland marine and mobile property insurance, oceanmarine insurance, boat insurance, motorcycle insurance, farm vehicleinsurance, aircraft or aviation insurance, and other types of insuranceproducts.

Other Matters

Although the text herein sets forth a detailed description of numerousdifferent embodiments, it should be understood that the legal scope ofthe invention is defined by the words of the claims set forth at the endof this patent. The detailed description is to be construed as exemplaryonly and does not describe every possible embodiment, as describingevery possible embodiment would be impractical, if not impossible. Onecould implement numerous alternate embodiments, using either currenttechnology or technology developed after the filing date of this patent,which would still fall within the scope of the claims. 101641 In oneaspect, autonomous or semi-autonomous vehicle; telematics;interconnected home; mobile device; and/or other data, including thatdiscussed elsewhere herein, may be collected or received by an insuranceprovider remote server, such as via direct or indirect wirelesscommunication or data transmission, after a customer affirmativelyconsents or otherwise opts into an insurance discount, reward, or otherprogram. The insurance provider may then analyze the data received withthe customer's permission to provide benefits to the customer. As aresult, risk averse customers may receive insurance discounts or otherinsurance cost savings based upon data that reflects low risk behaviorand/or technology that mitigates or prevents risk to (i) insured assets,such as autonomous or semi-autonomous vehicles, and/or (ii) autonomousor semi-autonomous vehicle operators or passengers.

It should also be understood that, unless a term is expressly defined inthis patent using the sentence “As used herein, the term ‘_____’ ishereby defined to ” or a similar sentence, there is no intent to limitthe meaning of that term, either expressly or by implication, beyond itsplain or ordinary meaning, and such term should not be interpreted to belimited in scope based upon any statement made in any section of thispatent (other than the language of the claims). To the extent that anyterm recited in the claims at the end of this disclosure is referred toin this disclosure in a manner consistent with a single meaning, that isdone for sake of clarity only so as to not confuse the reader, and it isnot intended that such claim term be limited, by implication orotherwise, to that single meaning. Finally, unless a claim element isdefined by reciting the word “means” and a function without the recitalof any structure, it is not intended that the scope of any claim elementbe interpreted based upon the application of 35 U.S.C. § 112(f).

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain embodiments are described herein as includinglogic or a number of routines, subroutines, applications, orinstructions. These may constitute either software (code embodied on anon-transitory, tangible machine-readable medium) or hardware. Inhardware, the routines, etc., are tangible units capable of performingcertain operations and may be configured or arranged in a certainmanner. In example embodiments, one or more computer systems (e.g., astandalone, client or server computer system) or one or more hardwaremodules of a computer system (e.g., a processor or a group ofprocessors) may be configured by software (e.g., an application orapplication portion) as a hardware module that operates to performcertain operations as described herein.

In various embodiments, a hardware module may be implementedmechanically or electronically. For example, a hardware module maycomprise dedicated circuitry or logic that is permanently configured(e.g., as a special-purpose processor, such as a field programmable gatearray (FPGA) or an application-specific integrated circuit (ASIC) toperform certain operations, A hardware module may also compriseprogrammable logic or circuitry (e.g., as encompassed within ageneral-purpose processor or other programmable processor) that istemporarily configured by software to perform certain operations. Itwill be appreciated that the decision to implement a hardware modulemechanically, in dedicated and permanently configured circuitry, or intemporarily configured circuitry (e.g., configured by software) may bedriven by cost and time considerations.

Accordingly, the term “hardware” should be understood to encompass atangible entity, be that an entity that is physically constructed,permanently configured (e.g., hardwired), or temporarily configured(e.g., programmed) to operate in a certain manner or to perform certainoperations described herein. Considering embodiments in which hardwareis temporarily configured (e.g., programmed), the hardware need not beconfigured or instantiated at any one instance in time. Software mayaccordingly configure a processor, for example, to constitute aparticular hardware module at one instance of time and to constitute adifferent hardware module at a different instance of time. Hardwareelements can provide information to, and receive information from, otherhardware elements. Accordingly, the described hardware may be regardedas being communicatively coupled.

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions, The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules. Similarly, the methods or routinesdescribed herein may be at least partially processor-implemented. Theperformance of certain of the operations may be distributed among theone or more processors, not only residing within a single machine, butdeployed across a number of machines. In some example embodiments, theprocessor or processors may be located in a single location (e.g.,within a home environment, an office environment or as a server farm),while in other embodiments the processors may be distributed across anumber of locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata. represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation. As used herein any reference to “one embodiment” or “anembodiment” means that a particular element, feature, structure, orcharacteristic described in connection with the embodiment may beincluded in at least one embodiment. The appearances of the phrase “inone embodiment” in various places in the specification are notnecessarily all referring to the same embodiment. Some embodiments maybe described using the expression “coupled” and “connected” along withtheir derivatives. For example, some embodiments may be described usingthe term “coupled” to indicate that two or more elements are in directphysical or electrical contact. The term “coupled,” however, may alsomean that two or more elements are not in direct contact with eachother, but vet still co-operate or interact with each other. Theembodiments are not limited in this context.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. In addition,use of the “a” or “an” are employed to describe elements and componentsof the embodiments herein. This is done merely for convenience and togive a general sense of the description. In this description, and theclaims that follow, the singular also includes the plural unless it isobvious that it is meant otherwise. This detailed description is to beconstrued as exemplary only and does not describe every possibleembodiment, as describing every possible embodiment would beimpractical, if not impossible. One could implement numerous alternateembodiments, using either current technology or technology developedafter the filing date of this application.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs forsystem and a method for assigning mobile device data to a vehiclethrough the disclosed principles herein. Thus, while particularembodiments and applications have been illustrated and described, it isto be understood that the disclosed embodiments are not limited to theprecise construction and components disclosed herein. Variousmodifications, changes and variations, which will be apparent to thoseskilled in the art, may be made in the arrangement, operation anddetails of the method and apparatus disclosed herein without departingfrom the spirit and scope defined in the appended claims.

The particular features, structures, or characteristics of any specificembodiment may be combined in any suitable manner and in any suitablecombination with one or more other embodiments, including the use ofselected features without corresponding use of other features. Inaddition, many modifications may be made to adapt a particularapplication, situation or material to the essential scope and spirit ofthe present invention. It is to be understood that other variations andmodifications of the embodiments of the present invention described andillustrated herein are possible in light of the teachings herein and areto be considered part of the spirit and scope of the present invention.

What is claimed is:
 1. A computer-implemented method for determining thestatus of autonomous operation features of an autonomous orsemi-autonomous vehicle, comprising: receiving, at one or moreprocessors, a signal indicating a request to determine an operatingstatus of one or more autonomous operation features of the autonomous orsemi-autonomous vehicle; determining, by one or more processors, aconfiguration of the one or more autonomous operation features;presenting, by one or more processors, a test signal to the one or moreautonomous operation features; receiving, at one or more processors, oneor more response signals from the one or more autonomous operationfeatures; determining, by one or more processors, the operating statusof the one or more autonomous operation features based upon the receivedone or more response signals; generating, by one or more processors, anoperating status report indicating the operating status of the one ormore autonomous operation features; and storing, in a computer-readablenon-transitory memory, the operating status report for subsequent use.2. The computer-implemented method of claim 1, further comprising:transmitting, via a network, the generated operating status report to aserver; determining, by one or more processors of the server, anadjustment to one or more risk levels associated with operation of theautonomous or semi-autonomous vehicle; determining, by one or moreprocessors of the server, an adjustment to a cost associated with aninsurance policy associated with the autonomous or semi-autonomousvehicle based upon the determined adjustment to the one or more risklevels; causing, by one or more processors of the server, the adjustmentto the cost associated with the insurance policy to be implemented. 3.The computer-implemented method of claim 2, wherein the cost associatedwith the insurance policy includes at least one of the following: apremium, a discount, a surcharge, a rate level, a cost based upon adistance traveled, a cost based upon a vehicle trip, or a cost basedupon a. duration of vehicle operation.
 4. The computer-implementedmethod of claim 2, further comprising: receiving, at the one or moreprocessors of the server, one or more indications of maintenanceperformed on the autonomous or semi-autonomous vehicle, whereindetermining the adjustment to the cost associated with the insurancepolicy is further based upon the received one or more indications ofmaintenance.
 5. The computer-implemented method of claim 1, wherein theone or more autonomous operation features comprise one or more sensorsdisposed within the autonomous or semi-autonomous vehicle.
 6. Thecomputer-implemented method of claim 1, wherein the signal indicatingthe request to determine the operating status of the one or moreautonomous operation features is automatically generated by a processorupon the occurrence of an event.
 7. The computer-implemented method ofclaim 6, wherein the event includes one or more of the following:receipt of a command to start the vehicle, receipt of a command to shutoff the vehicle, receipt of an indication of a collision involving thevehicle, or receipt of an indication of damage to the vehicle.
 8. Thecomputer-implemented method of claim 1, wherein: the signal indicatingthe request to determine the operating status of the one or moreautonomous operation features is received from a mobile devicecommunicatively connected to the autonomous or semi-autonomous vehicle:and the system status module is executed by one or more processors of anon-board computer disposed within the autonomous or semi-autonomousvehicle.
 9. The computer-implemented method of claim 1, wherein thesignal indicating the request to determine the operating status of theone or more autonomous operation features is received from aspecial-purpose computing device communicatively connected to theautonomous or semi-autonomous vehicle.
 10. The computer-implementedmethod of claim 1, further comprising: when operation of one or moresensors disposed within the vehicle are determined to be impaired byenvironmental factors, generating, by one or more processors, aremediation signal; and presenting the remediation signal to one or moreremediation components disposed within the vehicle, wherein the one ormore remediation components are configured to remediate impairments ofthe one or more sensors by environmental factors.
 11. Thecomputer-implemented method of claim 10, wherein the one or more sensorsare impaired by blockage by one or more of the following: snow, ice,rain, dirt, mud, or condensation.
 12. The computer-implemented method ofclaim 1, further comprising: diagnosing, by one or more processors, oneor more errors with at least one autonomous operation feature based uponthe received one or more response signals from the one or moreautonomous operation features; and correcting, by one or moreprocessors, the diagnosed one or more errors with the at least oneautonomous operation feature.
 13. The computer-implemented method ofclaim 12, Wherein correcting the diagnosed one or more errors with theat least one autonomous operation feature includes calibrating at leastone sensor disposed within the vehicle based upon the received one ormore response signals from the one or more autonomous operationfeatures.
 14. The computer-implemented method of claim 12, wherein theone or more errors include at least one of the following: a softwareerror, an out-of-date software version, or a software incompatibility.15. The computer-implemented method of claim 1, wherein generating theoperating status report includes generating a certification of theoperating status of the one or more autonomous operation features. 16.The computer-implemented method of claim 1, wherein the one or moreautonomous operation features of the autonomous or semi-autonomousvehicle are related to at least one of the following: steering;accelerating; braking; monitoring blind spots; presenting a collisionwarning; adaptive cruise control; parking; driver alertness monitoring;driver responsiveness monitoring; pedestrian detection; artificialintelligence; a back-up system; a navigation system; a positioningsystem; a security system; an anti-hacking measure; a theft preventionsystem; or remote vehicle location determination.
 17. A computer systemfor determining the status of autonomous operation features of anautonomous or semi-autonomous vehicle, comprising: one or moreprocessors; one or more sensors communicatively connected to the one ormore processors; and a program memory coupled to the one or moreprocessors and storing executable instructions that when executed by theone or more processors cause the computer system to: receive a signalindicating a request to determine an operating status of one or moreautonomous operation features of the autonomous or semi-autonomousvehicle; determine a configuration of the one or more autonomousoperation features; present a test signal to the one or more autonomousoperation features; receive one or more response signals from the one ormore autonomous operation features; determine the operating status ofthe one or more autonomous operation features based upon the receivedone or more response signals; generate an operating status reportindicating the operating status of the one or more autonomous operationfeatures; and store the operating status report for subsequent use. 18.The computer system of claim 17, wherein the program memory furtherstores executable instructions that cause the computer system to:generate a remediation signal when operation of one or more sensorsdisposed within the vehicle are determined to be impaired byenvironmental factors; and present the remediation signal to one or moreremediation components disposed within the vehicle, wherein the one ormore remediation components are configured to remediate impairments ofthe one or more sensors by environmental factors.
 19. A tangible,non-transitory computer-readable medium storing instructions fordetermining the status of autonomous operation features of an autonomousor semi-autonomous vehicle that, when executed by at least one processorof a computer system, cause the computer system to: receive a signalindicating a request to determine an operating status of one or moreautonomous operation features of the autonomous or semi-autonomousvehicle; determine a configuration of the one or more autonomousoperation features; present a test signal to the one or more autonomousoperation features; receive one or more response signals from the one ormore autonomous operation features; determine the operating status ofthe one or more autonomous operation features based upon the receivedone or more response signals; generate an operating status reportindicating the operating status of the one or more autonomous operationfeatures; and store the operating status report for subsequent use. 20.The tangible, non-transitory computer-readable medium of claim 19,wherein the instructions further cause the computer-system to: diagnoseone or more errors with at least one autonomous operation feature basedupon the received one or more response signals from the one or moreautonomous operation features; and correct the diagnosed one or moreerrors with the at least one autonomous operation feature.